EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN … · EFFECTS OF TERMS OF TRADE SHOCKS ON THE...
Transcript of EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN … · EFFECTS OF TERMS OF TRADE SHOCKS ON THE...
EFFECTS OF TERMS OF TRADE SHOCKS
ON THE RUSSIAN ECONOMY
No. 48 / October 2019
WORKING PAPER SERIES
Natalia Turdyeva
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 2
Cover photo: Shutterstock.com
Address: 12 Neglinnaya street, Moscow, 107016
Tel.: +7 495 771-91-00, +7 495 621-64-65 (fax)
Website: www.cbr.ru
© Bank of Russia, 2019
All rights reserved. The views expressed in this Paper (these papers) are solely those of the authors
and do not necessarily reflect the official position of the Bank of Russia. The Bank of Russia assumes no
responsibility for the contents of the Paper (papers). Any reproduction of these materials is permitted only
with the express consent of the authors.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 3
Effects of terms of trade shocks on the Russian economy
Natalia Turdyeva
Bank of Russia
October 7, 2019
Abstract
The principal interest of the paper is the quantification of terms of trade shock response
of the Russian economy on a detailed computable general equilibrium (CGE) model calibrated
with Russian input-output data.
The results suggest a decrease of welfare of the representative consumer and real GDP
with the deterioration of the terms of trade. In the Central scenario (a 10% decrease in the world
price of crude oil, a 3% decrease in the world price of natural gas and an 8% decrease in the
world price of petroleum products) welfare of the representative consumer decreases by -1,17%
of benchmark consumption level or -0,58% of the base year GDP in the comparative static model.
Percentage change of the GDP in the Central scenario of the comparative static model is of the
same magnitude as representative agent’s decrease in welfare in terms of the benchmark GDP:
-1,55%.
Welfare changes associated with the Central scenario of the steady-state model, where
capital stock adjusts to its long-term level, indicate a significant decrease in the welfare of the
representative agent up to -2,64% of benchmark consumption level or -1,23% of the base year
GDP. Percentage change of the GDP in the Central scenario of the steady-state model exceeds
representative agent’s decrease in welfare in terms of the benchmark GDP: -2,51%.
The model was validated by historical simulation with observed levels of exogenous
parameters, mimicking change in economic environment from 2011 to 2015. The results of the
historical simulation stress the importance of fiscal parameters (i.e. export taxes) in analysis of
production behaviour of Russian extraction industries.
Key words: terms of trade, oil price shock, computable general equilibrium models, input-
output table, industry output; CGE model validation.
JEL classification: F17, C68, D58.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 4
Contents
1. INTRODUCTION ....................................................................................................... 6
2. LITERATURE REVIEW ............................................................................................. 7
THE EFFECT OF THE SHOCK OF THE TERMS OF TRADE ON THE OUTPUT OF INDUSTRIES ............. 7
TOTAL OUTPUT AND REAL EXCHANGE RATE ......................................................................... 9
ESTIMATING EFFECTS OF A TOT SHOCK WITH A GENERAL EQUILIBRIUM MODEL ..................... 11
MODELS OF COMPUTABLE GENERAL EQUILIBRIUM FOR THE RUSSIAN ECONOMY ................... 12
3. MODEL DESCRIPTION .......................................................................................... 12
3.1. THE COMPARATIVE STATIC MODEL ............................................................ 13
ECONOMIC AGENTS .......................................................................................................... 13
INDUSTRIES ..................................................................................................................... 15
3.2. STEADY-STATE MODEL ................................................................................. 16
4. BENCHMARK DATASET ....................................................................................... 17
4.1. SOCIAL ACCOUNTING MATRIX ..................................................................... 17
4.2. ELASTICITIES................................................................................................... 18
5. RESULTS: TERMS OF TRADE DECREASE ......................................................... 20
5.1. SCENARIO DEFINITION ................................................................................... 20
5.2. SIMULATIONS RESULTS: COMPARATIVE STATIC MODEL ........................ 21
5.3. SIMULATIONS RESULTS: STEADY-STATE MODEL ..................................... 22
5.4. CHANGES ON THE INDUSTRY LEVEL ........................................................... 24
OUTPUT CHANGES ........................................................................................................... 24
PRICE CHANGES .............................................................................................................. 25
5.5. VALIDATION OF THE MODEL: HISTORICAL SIMULATIONS ....................... 27
6. CONCLUSION ......................................................................................................... 31
REFERENCES .............................................................................................................. 32
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 5
APPENDIX I. ANALYTICAL STRUCTURE OF THE MODEL ...................................... 37
EQUATIONS ..................................................................................................................... 37
HOUSEHOLD’S PROBLEM .................................................................................................. 37
GOVERNMENT BUDGET ..................................................................................................... 38
SUPPLY FOR DOMESTIC AND EXPORT MARKETS .................................................................. 38
BALANCE OF PAYMENTS ................................................................................................... 39
ARBITRAGE CONDITIONS .................................................................................................. 39
MARKET EQUILIBRIUM CONDITIONS.................................................................................... 41
SYMBOL MAP ................................................................................................................... 42
APPENDIX II DATA AND PARAMETRIZATION .......................................................... 45
INDUSTRY LIST ................................................................................................................. 45
APPENDIX III SIMULATIONS DESIGN ........................................................................ 47
APPENDIX IV SIMULATION RESULTS ....................................................................... 48
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 6
1. Introduction
The focus of this paper is on the output response on detailed industry level. The
aim is to study propagation of oil price shock in the simplest general equilibrium settings
possible, in a small open nested-CES economy with a representative agent, perfectly
competitive cost-minimizing producers and inelastic factor supplies. This paper examines
the impact of changes in world prices on the Russian economy. In particular, I am
interested in the change in production as a result of changes in world prices for the main
Russian export and import commodities. The model presented in the paper belongs to
the class of computable general equilibrium (CGE) models, it has a detailed industry
structure, which allows tracing the effect of changes in world prices on all aspects of the
Russian economy.
This article examines the impact of changes in world prices on the Russian
economy. In particular, I am interested in the change in production as a result of changes
in world prices for the main Russian export and import commodities.
A number of recent macro studies ((Atalay 2017), (Acemoglu, Ozdaglar, and
Tahbaz-salehi 2017) (Burstein, Kurz, and Tesar 2008)) stressed importance of explicit
introduction of the intermediates in the models assessing effects of external shocks,
which is a well-established practice in the computable general equilibrium methodology.
Models of this class permit introduction of rich details and complex production structures
as well as optimizing behaviour of economic agents.
The model presented in the paper belongs to the class of computable general
equilibrium (CGE) models, it has a detailed industry structure, which allows tracing the
effect of changes in world prices on all aspects of the Russian economy.
The results suggest a decrease of welfare of the representative consumer and real
GDP with the deterioration of the terms of trade. In the Central scenario (a 10% decrease
in the world price of crude oil, a 3% decrease in the world price of natural gas and an 8%
decrease in the world price of petroleum products) welfare of the representative
consumer decreases by -1,17% of benchmark consumption level or -0,58% of the base
year GDP in the comparative static model. Percentage change of the GDP in the Central
scenario of the comparative static model is of the same magnitude as representative
agent’s decrease in welfare in terms of the benchmark GDP: -1,55%.
Welfare changes associated with the Central scenario of the steady-state model
indicate a significant decrease in the welfare of the representative agent up to -2,64% of
benchmark consumption level or -1,23% of the base year GDP. Percentage change of
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 7
the GDP in the Central scenario of the steady-state model exceeds representative agent’s
decrease in welfare in terms of the benchmark GDP: -2,51%. The GDP response in the
steady-state model is in line with estimates obtained in compatible work (Полбин 2017).
These results exceed welfare changes in the Central scenario of the static model,
and we can refer to these values as upper bound of possible changes in welfare in the
dynamic modelling exercise (Rutherford and Tarr 2003).
2. Literature review
The effect of the shock of the terms of trade on the output of industries
The dependence of the Russian economy on oil prices manifests itself in 2014-
2015 (see Figure 1), when, following the reduction in oil prices and the restriction of
access to capital markets, Russia's economy entered a recession (World Bank Group
2015).
Figure 1. Real GDP of the Russian Federation, in % to the previous year
Source: Rosstat.
The main reasons for the decline in production in 2015 were a sharp drop in oil
prices, a subsequent depreciation of the rouble with a corresponding increase in inflation.
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016GD
P c
han
ge, %
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 8
The situation was complicated by the loss of investor confidence resulting from economic,
political and external economic circumstances.
The decline in prices for oil and oil products, which are the key Russian exports,
while maintaining world prices for goods imported into Russia, led to a reduction in the
ratio of prices of export goods to the prices of imported goods, or terms of trade (Reinsdorf
2010).
Numerous studies (International Monetary Fund 2017), (Cavalcanti, Mohaddes, and
Raissi 2015) find that GDP growth (see Figure 2) and other macroeconomic characteristics
of commodity-exporting countries, including Russia, depend to a greater extent on
changing terms of trade than comparable countries, which are not commodity exporters.
Figure 2. Contribution of terms of trade to GDP per capita change, commodity-
exporting countries and EMDE, in average for developing countries.
Source: International Monetary Fund, (International Monetary Fund 2017), p. 74.
There are various estimates of the extent to which the shocks of the terms of trade
cause business cycles in developing countries. For a long time economists considered
that up to 30% of the change in output and other macroeconomic indicators was due to
changes in terms of trade (Mendoza 1995) and (Kose 2002). The latest estimates
(Schmitt-Grohé and Uribe 2018) significantly reduce this estimate, referring to less than
10% of the relationship between changes in terms of trade and the movement of gross
output. Despite the uncertainty about the impact of the terms of trade on the economy of
developing countries on average, the mechanisms of influence are well described. Idrisov
et al. (Идрисов, Пономарев, and Синельников-Мурылёв 2015) note two main channels
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 9
of the impact of terms of trade on the Russian economy: a reduction in disposable income
and a devaluation of the rouble.
The impact of the real rouble exchange rate on the macroeconomic parameters of
the economy and aggregate output has always been in the focus of attention of
economists. Let us consider below a few works devoted to this topic in general and in
application to the Russian economy.
Total output and real exchange rate
There is no consensus in the theoretical literature on the impact of a change in the
exchange rate of the national currency on the real output. Gylfason and Schmid (Gylfason
and Schmid 1983) discuss a possible channel for the negative impact of the weakening
of the national currency on aggregate output: in the case of a large share of imports in
intermediate consumption, devaluation leads to an increase in the costs of domestic
production, which can cause a fall in supply, as a consequence, a reduction in the
equilibrium output. This channel of influence is the more important, the less the elasticity
of substitution of imported intermediates by domestic in the production processes of
domestic firms.
For the economy as a whole, the substitution of imported goods by domestic
largely depends on the structure of the preferences of households: if imports and
domestically produced goods are easily substituted in the consumption, then with the
increase in import prices there will be a switch to consumption of domestic goods, and,
as shown in the work of Kadochnikov et al. (Кадочников, Синельников-Мурылёв, and
Четвериков 2003), this will lead to an increase in the domestic output. If domestic and
imported goods are compliments and do not replace each other in consumption, the
increase in import prices will be accompanied by a decrease in demand for home
products, which is due to the predominance of the income effect over the substitution
effect, and as a result, the demand for home products will decrease.
An important channel of propagation of exchange rate swings on the aggregate
output may be the relationship of exchange rate and investment demand. As noted in a
number of growth models with technology adaptation (Easterly et al. 1994), the
weakening of the national currency leads to a rise in the cost of borrowing technology.
This leads to a drop in investment, and, ultimately, to a decrease in the aggregate output.
As Badasen and co-authors (Бадасен, Картаев, and Хазанов 2015) note, this channel
of influence is especially important for developing economies in which technology import
plays an important role.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 10
In the works of Aghion and co-authors (Aghion, Bacchetta, and Banerjee 2000),
Greenwald and Stiglitz (Greenwald and Stiglitz 1993), Gatti et al. (Gatti et al. 2007), it is
shown that in the case of a large volume of borrowings of the private sector in foreign
currency, after a devaluation, debt servicing becomes more complicated due to its growth
in the national currency. This can lead to a reduction in the cumulative output.
The general direction of the change in the aggregate and industry output caused
by the exchange rate changes depends on the conditions prevailing at a particular
moment in the given economy, and economic theory does not give a single answer to the
question of the direction of change. In part, this thesis is confirmed by the heterogeneous
results obtained for the Russian economy in the studies of various authors over the past
few years.
Dynnikova (Дынникова 2000), on the basis of the theoretical model, came to the
conclusion that in the period from 1993 to 1997, the strengthening of the real exchange
rate of the rouble was accompanied by an increase in output, presumably due to lower
prices for imported components and intermediate goods.
Kontorovich's empirical findings (Конторович 2001) show that strengthening the
real rouble/dollar exchange rate by 1% with a lag of several months is accompanied by a
reduction in the intensity index of industrial production by approximately 0.2%.
In the work of Kadochnikov et al. (Кадочников, Синельников-Мурылёв, and
Четвериков 2003), a link was made between the strengthening of the national currency
and the growth in demand for imports: the strengthening of the real exchange rate by 1%
leads to the replacement of domestic goods with imports by 0.77% on average in the
economy.
Kartayev (Картаев 2009) concluded that the weakening of the national currency
by 1% leads to an increase in real GDP of Russia by 0.66%. From the point of view of
sector dynamics, it was concluded that the weakening of the rouble does not lead to
changes in the production of the extractive industry, but at the same time, it leads to an
increase in the output of the manufacturing industry.
Vdovichenko et al. (Вдовиченко, Дынникова, and Субботин 2003) also
expressed the idea that the manufacturing industry reacts more strongly to fluctuations in
exogenous factors, including the real exchange rate. From the point of view of the
difference in the sectoral response to the change in the real exchange rate, the industries
were divided into three groups: losers of the strengthening the real exchange rate (fuel,
wood pulp and paper, chemical and petrochemical, non-ferrous metallurgy), insensitive
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 11
to real exchange rate changes (food and mechanical engineering) and winners (light
industry, ferrous metallurgy, construction materials industry and electric power industry).
In the work of Badasen, Kartaev, and Khazanov (Бадасен, Картаев, and Хазанов
2015), based on econometric research, it was concluded that when the exchange rate of
the rouble depreciates, the most favourable effect is on export-oriented industries, as well
as on industries with a low share of imports in costs.
The studies referred above generally agree with the positive influence of the
relative weakening of the domestic currency on domestic output. But it should be noted,
that in a case of a ToT shock, usually both channels of influence are present: income
effect and exchange rate. Thus, in order to simulate effect of a ToT deterioration of the
detailed industry structure of the Russian economy there is a need of a structural model.
One of possible solutions is use of the computable general equilibrium model.
Estimating effects of a ToT shock with a general equilibrium model
Computable (applied) general equilibrium model is a system of equations
describing behaviour of economic agents in an economy. The numerical parameters of
the model equations are based on statistical data of one year or averaged data over
several years. The procedure for calculating the parameters of a model is called
calibration. The model is calibrated so that the base year data is obtained as the initial
equilibrium.
Scenario forecasts are set by changing one or several controls, for example, by
changing exogenous world prices for export or import goods. After changing the controls,
a new equilibrium is obtained. The new equilibrium reflects the effect of the proposed
changes in the controls. Resulting changes in endogenous variables are obtained by
comparing the basic data set and the new equilibrium obtained as a result of the
experiment.
Models of computable general equilibrium (CGE models) have traditionally been
the most effective and most widely used tool for assessing possible changes in foreign
trade (Hertel 2013), taxation (Dixon and Rimmer 2016), public expenditure (Holmøy and
Strøm 2013), social security (Fehr 2016), demography (Zodrow and Diamond 2013),
immigration (Fehr et al. 2013), labour markets (Dixon, Koopman, and Rimmer 2013),
environment (Böhringer et al. 2015), as well as assessing the effects of natural
(Shibusawa et al. 2011) and man-made disasters (Rose and Liao 2005). CGE models
are the only practical way to quantify these effects at the level of industries, regions
(Giesecke and Madden 2013) and socio-economic groups (Horridge et al. 2013).
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 12
Even at the dawn of its existence, computable general equilibrium models were
used to assess the effects of the shock of terms of trade on the welfare, changes in output
and factor income (Devarajan and Robinson 2013). Subsequently, a variety of studies
were conducted both at the level of one country (Dixon, Koopman, and Rimmer 2013),
often in a regional breakdown (Dong et al. 2017), or in the framework of global models
(Timilsina 2015).
Models of computable general equilibrium for the Russian economy
Examples of the use of computable general equilibrium models for Russia include:
Makarov (Макаров 1999), Zemnitsky (Земницкий 2003), Bakhtizin (Бахтизин 2003),
Alekseev, Turdyeva, Yudaeva (Alekseev, Turdyeva, and Yudaeva 2003), Alekseev,
Sokolov, Turdyeva, Yudaeva (Alekseev et al. 2004), Jensen, Rutherford and Tarr
(Rutherford and Tarr 2004), (D. G. Tarr and Rutherford 2004), (Helm and Rutherford
2004), Rutherford, Tarr, Shepotilo (D. G. Tarr, Shepotylo, and Kouduyarov 2005),
Alekseyev et al. (Алексеев et al. 2004),, Besstremyannaya, Bakhtizin (Besstremyannaya
and Bakhtizin 2006), Volchkova and others . (Волчкова et al. 2006), Rutherford and Tarr
(D. Tarr 2006), Kolik, Radziwill, Turdiyeva (Kolik, Radziwill, and Turdyeva 2015),
Bohringer et al. (Böhringer et al. 2015).
The effects of the shock of the terms of trade and the subsequent recession of
2014-2015 on welfare distribution in Russia are considered in the work of Bussolo and
Luongo (Bussolo and Luongo 2017). The authors concluded that a 50% reduction in oil
prices would lead to a significant decline in oil production and refining (-13%), a reduction
in construction industry production (-5%) and transport (-1.3%). The main gain will be for
the export industries of manufacturing (+ 12.7%), agriculture (+ 9.5%), other
manufacturing (+ 8.2%) and other extractive industries (+ 5.1%), and the food industry (+
2.3%). Among other consequences, the authors note a fall in the well-being of the
population by 6.88% in terms of consumption.
3. Model Description
I present two models: the core comparative static model with inelastic factor supply
and a steady-state model with a variable capital stock. The steady-state model is an
extension of the comparative static model, it solves for time-invariant capital stock, i.e.
cost of investment equals the discounted stream of rents on installed capital. The goal of
the steady-state model is to “evaluate the upper bound of welfare gains in a Solow type
model” (Rutherford and Tarr 2003).
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 13
3.1. The comparative static model
The structure of the core model is close to the CRTS model used in Böhringer et
al. (Böhringer et al. 2015). The model is based on optimizing behaviour of all economic
agents, supply and demand balances in all markets for goods, services, and factors.
Budgets are balanced for all agents.
The algebraic formulation presented in the appendix corresponds to the core
model of a small open nested-CES economy with perfectly competitive cost-minimizing
producers and inelastic factor supplies. Economic agents resented in the model are
households, enterprises, investment sector, and government. Consumers of final and
intermediate goods differentiate between domestic and imported goods, i.e. the
Armington (Armington 1969) assumption is used (Figure 3).
Figure 3. Structure of products differentiation in the model.
Source: the author
Economic agents
Economic agents of the model are: a representative household, enterprises, the
government and a savings-investment bank (see Figure 4). The government collects
direct and indirect taxes with fixed ad-valorem tax rates, saves an amount equal to trade
surplus in the base year in foreign currency (V̅), then saves a fixed portion of the tax
revenue in the domestic savings-investment bank, and purchases goods (g𝑖) on the final
market.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 14
Figure 4. Structure of income and spending of economic agents in the model
Source: the author
I assume that labour belong to households and capital belong to enterprises.
Enterprises receive all capital income, pay direct corporate taxes (the corporate profit tax
and the resource extraction tax), save a fixed portion of an after-tax capital earnings and
transfers the rest to shareholders. I assume that there is no foreign ownership of Russian
companies, thus all payments to shareholders are transferred to the domestic
households.
The representative domestic household receives labour remuneration and share
of profit from the enterprises (discussed above). Households pay personal income tax,
saves a portion of the after-tax income and uses the rest on private consumption (c𝑖).
The savings-investment bank receives private, enterprise, and government
savings. Savings of all economic agents in the model are savings-driven (Lofgren,
Thomas, and El-said 2002), in other words, each economic agent saves a fixed share of
its budget. The savings-investment bank spends all available funds on purchase of goods
on the final market (i𝑖).
There is no international ownership of factors, i.e. model does not account for non-
zero net factor payments. Default external closure of the core model states that foreign
savings of the government is fixed and exchange rate is fully flexible. Government’s
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 15
foreign savings are fixed on the base year level V̅, which equals to the current account
surplus (or, in the case of NFP=0, to the trade surplus).
Industries
There are 52 industries (Table 6) producing goods and services, each described
by a representative firm. Cost-minimizing firms operate in free-entry markets, which leads
to zero profit, i.e. marginal returns for an individual firm equal marginal cost.
Production technologies are characterized by constant returns to scale. Output (Y)
is a Leontief (𝜎𝑌 = 0)1, combination of value added (VA) and intermediate goods (INT).
Value added is a Cobb-Douglas (𝜎𝑉𝐴 = 1) aggregate of primary factors (mobile labour
(L), mobile (K) and specific capital (SK)) and intermediate goods and services (INT) (see
Figure 5).
Intermediate goods are a bundle of imported (mij – imports of commodity i for
industry j) and domestically produced intermediates (dij). Bundling of domestic and
imported intermediates is done for each industry and each type of good separately. All
bundling techniques for the intermediate products are described by CES functions and
share the same low (Atalay 2017) elasticity of substitution between domestic and
imported goods (𝜎𝑚 = 0.4), share parameters for each industry i and each good j are
calibrated on detailed information provided by Russian input-output tables2. Relatively
low value of elasticity of substitution between domestic and imported intermediates
reflects high level of complementarity of imports in firms’ intermediate consumption
(Березинская and Ведев 2015).
Domestically produced goods (Y) are split between domestic (D) and export
markets (X) on the basis of relative prices at home and export markets. This
transformation, i.e. a decision of an exporter, is described by the constant elasticity of
transformation (CET) function. Default value of elasticity of transformation equals 0.15.
This relatively low level of the elasticity of transformation corresponds to values reported
1 𝜎𝑌 – is the elasticity of substitution between value added (VA) and intermediate consumption
(INT) in the upper-level production function. Notational convention: 𝜎 (sigma) - denotes elasticity
of substitution in various production and bundling functions; (eta)- elasticity of transformation between domestic goods for domestic market and exports. Please note, that limit case of a CES
function with elasticity of substitution 𝜎 = 0 is the Leontief function, and 𝜎 = 1 is the Cobb-Douglas function. 2 Base input-output tables for the Russian Federation were estimated for year 2011
(http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/accounts/#), more on data sources in the relevant chapter. Information on the composition of intermediate consumption is provided by use tables for domestic and imported goods.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 16
in (Tokarick 2014) and (IMF 2017) and reflects problems in reallocation of resources from
domestic supply to export markets that Russian economy faces.
Domestically produced goods for the domestic market (D), are bundled with
imports (M). The composite good (A) is supplied to the domestic market where it serves
final demand by the representative agent. The bundling of domestic and imported goods
is described by constant elasticity of substitution (CES) function with elasticity (𝜎𝐴 = 4).
This value is close to the average of Armington substitution elasticities between domestic
and imported goods in GTAP 9 database (Aguiar, Narayanan, and McDougall 2016).
Figure 5. Structure of industrial production and supply of composite goods for the final
market.
Source: Author
3.2. Steady-state model
The steady-state model is an extension of the core comparative static model. The
goal of the steady-state calculation is to evaluate the upper bound (Rutherford and Tarr
2003) on welfare changes associated with terms of trade change for the Russian
economy.
In the comparative static model the price of capital varies, while total supply of
capital is fixed. In the steady-state model the mobile capital stock and investment demand
are endogenously determined while the price of capital is constant. In other words, the
steady-state model solves for time-invariant capital stock. In the steady-state model
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 17
optimal capital stock is such that cost of investment equals the discounted stream of rents
on installed capital3. “This can be viewed as a multi-sector version of the “golden rule”
equilibrium” (Rutherford and Tarr 2003).
4. Benchmark dataset
The dataset for the model consists of two sets: economic indicators, which
describe economy of the Russian Federation for the base year (2011) in the form of the
Social accounting matrix (SAM) (see part 4.1) and the second set of behavioural
parameters derived from the relevant literature, which consists of different elasticities of
substitution (see part 4.2).
4.1. Social accounting matrix
The social accounting matrix for the model describes a snapshot of the economic
activities of Russia at year 2011, which is the base year in our case. The SAM is a square
matrix, each account is represented by a row and a column (Pyatt 1991). Row entities
correspond to income of the respective account, while column depicts payments of the
account. Accounts of the SAM consist of production activities, goods, factors of
production, economic agents, and economic policy instruments. For more information on
the social accounting matrix format of representing the economic data see (Pyatt and
Round 1985).
Main sources of the data for the SAM are Russian Input-Output (IO) tables for
20114, as well as National accounts for 2011 (Росстат 2017). The Input-Output tables
consist of a resource table, use tables in buyers' and basic prices, use tables of
domestically produced and imported products, tables with transport and trade margins,
and a table of taxes. Sectoral and commodity details of the original tables were
aggregated to 52 commodity and industries (Table 6). Development of a dataset for a
CGE model from an IO table in well-documented process (Rutherford and Paltsev 1999).
The IO tables do not contain information on direct taxes and other transfers
between economic agents. This information was obtained from national accounts (see
Table 1).
3 In the present version of the model depreciation is set to zero. 4 Rosstat, 2017, Russian Input-Output Tables for year 2011, retrieved from (http://www.gks.ru/free_doc/new_site/vvp/baz-tev-2011.xlsx) on September 05th, 2019
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 18
Table 1. Transfers between economic agent in the model
Source: the author
An aggregated version of the SAM used in the model is presented in the appendix
(Table 14).
4.2. Elasticities
In this section I stick to the following notational convention: 𝜎 (sigma) – denotes
elasticity of substitution in various production and bundling functions; (eta) – elasticity
of transformation between domestic goods for domestic market and exports5.
Output in each industry is produced with a nested production function. The upper
nest is a Leontief combination of value added (VA) and intermediate goods (INT), 𝜎𝑌 = 0
– is the elasticity of substitution between value added (VA) and intermediate consumption
(INT) in the upper-level production function. This type of nested production function was
used in several models of the Russian economy, see (Böhringer et al. 2015).
Value added is a Cobb-Douglas aggregate of primary factors (mobile labour (L),
mobile (K) and specific capital (SK)) and intermediate goods and services (INT) (see
Figure 5). 𝜎𝑉𝐴 = 1 is the elasticity of substitution between different factors in production
of value added.
Domestic and imported intermediates are bundled in each industry and for each
type of good separately. All bundling techniques for the intermediate products are
described by CES functions and share the same low (Atalay 2017) elasticity of
substitution between domestic and imported goods (𝜎𝑚 = 0.4), share parameters for
each industry i and each good j are calibrated on detailed information provided by Russian
5 Please note, that limit case of a CES function with elasticity of substitution 𝜎 = 0 is the Leontief
function, and 𝜎 = 1 is the Cobb-Douglas function (K. J. Arrow et al. 1961).
government households enterprisessavings-
investmentexports
gov hh ent s-i row
government gov
households hh 22,2187
enterprises ent
savings-investment s-i 1,0882 7,041 6,6067
imports row 5,4872
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 19
input-output tables6. Relatively low value of elasticity of substitution between domestic
and imported intermediates reflects high level of complementarity of imports in firms’
intermediate consumption (Березинская and Ведев 2015).
Transformation of domestically produced goods (Y) between domestic (D) and
export markets (X) is described by the constant elasticity of transformation (CET)
function. Default value of elasticity of transformation equals 0.15. This relatively low
level of the elasticity of transformation corresponds to values reported in (Tokarick 2014)
and (IMF 2017) and reflects problems in reallocation of resources from domestic supply
to export markets that Russian economy faces.
The bundling of domestic and imported goods is described by constant elasticity
of substitution (CES) function with elasticity (𝜎𝐴 = 4). This value is close to the average
of Armington substitution elasticities between domestic and imported goods in GTAP 9
database (Aguiar, Narayanan, and McDougall 2016).
Table 2. Central values of elasticities in the model
Elasticity Description Value Reference
1 𝜂 elasticity of transformation between supply to domestic and export markets
0.15 (Tokarick 2014) (IMF 2017)
2 𝜎𝑚 elasticity of substitution between domestic and imported goods in intermediate consumption
0.4 (Atalay 2017)
3 𝜎𝑌 elasticity of substitution between value added and intermediate goods in the production function
0 (Böhringer et al. 2015)
4 𝜎𝑉𝐴 elasticity of substitution between different factors in production of value added
1 (Böhringer et al. 2015)
5 𝜎𝐴 elasticity of substitution between domestic and imported goods in the Armington aggregation function for production of final goods
4 (Aguiar, Narayanan, and
McDougall 2016).
Source: respective papers
6 Rosstat, 2017, Russian Input-Output Tables for year 2011, retrieved from
(http://www.gks.ru/free_doc/new_site/vvp/baz-tev-2011.xlsx) on September 05th, 2019. Information on the composition of intermediate consumption is provided by use tables for domestic and imported goods.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 20
5. Results: Terms of trade decrease
One of my principal interests is the quantification of terms of trade shock response
of the Russian economy on a detailed CGE model calibrated with Russian input-output
data. A number of studies ((Atalay 2017), (Acemoglu, Ozdaglar, and Tahbaz-salehi 2017)
(Burstein, Kurz, and Tesar 2008)) stressed importance of implicit introduction of the
intermediates in the models assessing effects of external shocks. The assessment of
effects of a terms of trade shock on the macro and industry level is completed with a help
of a detailed computable general equilibrium model. Models of this class permit
introduction of rich details and complexity of production structures as well as optimizing
behaviour of economic agents.
5.1. Scenario definition
The central scenario is a 10% decrease in world prices of crude oil, accompanied
by a 3% decrease in the world price of natural gas, and an 8% decrease in the world price
of petrochemical products.
Relationship between the world oil and gas prices
There is a growing literature on long-term relationship between global crude oil
and natural gas prices (Nick and Thoenes 2014). Recently, the long-run oil–gas price
relationship has been challenged quite often, as these two prices have shown evidence
of decoupling from each other (Ramberg et al. 2017). Based on (Zhang and Ji 2018), we
adopt factor of 0.3, describing relationship between change in the world price of oil and
change of the world price of natural gas. Thus, in our central scenario a 10% decrease in
the world price of oil is accompanied with a 3% change in the world price of natural gas.
Relationship between the world oil and oil products’ prices
Strong technological connections (Ramberg et al. 2017) between crude oil and oil
products dictates relatively high factor of 0,8, describing relationship between crude oil
and oil products world prices for Russian exports (Polanco Martínez, Abadie, and
Fernández-Macho 2018). In our central scenario, a 10% decrease in the world price of
crude oil is accompanied by an 8% decrease in the world price of oil products.
We cap present Central scenario as a composition of three scenarios: “Oil”,
“Natural gas” and “Petroleum products”. Each of these scenarios model decrease in the
world prices of one separate good. Thus, the Central scenario is summarized as a
simultaneous decrease in three world prices for Russian exports:
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 21
Crude oil (scenario “Oil”: decrease of the world price for crude oil by 10%);
Natural gas (scenario “Natural gas”: decrease of the world price for Natural
gas by 3%);
Petroleum products (scenario “Petroleum products”: decrease of the world
price for Petroleum products by 8%).
5.2. Simulations results: comparative static model
Overall economic impacts: static model, Central scenario
Overall economic impact for the Central scenario in the settings of the static model
are shown in the table below (Table 9). The results are presented for the Central scenario
and it’s components. Welfare changes associated with the Central scenario indicate a
significant decrease in the welfare of the representative agent up to -1,17% of benchmark
consumption level or -0,58% of the base year GDP.
Percentage change of the GDP in the Central scenario is of the same magnitude
as representative agent’s decrease in welfare in terms of the benchmark GDP (-1,54%).
Major driver of the decline in the GDP is government consumption (-4,28%), due
to fall in oil taxes (export tariffs). Decline in the household’s consumption (-1, 17%) reflects
households’ income decline, caused by decline in remuneration of mobile factors of
production (wage decreases by -1,33%, mobile capital rent – by -0,73%). The most
significant decline in income is the decline of -3,22% rent of the specific capital in the oil
industry. Investment decreases as well (by -0,87%). The only component of the final
demand that experiences growth is real aggregated exports (1,23%), partly due to
performance of the exchange rate (+4,24%).
The external closure of the model fixes trade balance in real terms and lets the
exchange rate to adjust to changes in relative prices of exported and imported goods.
The exchange rate is defined in units of local currency to units of foreign currency, thus
an increase in the value of the exchange rate means depreciation of the local (domestic)
currency. A decrease in the exchange rate means that domestic currency strengthens.
The Central scenario is associated with a 4,24% increase in the exchange rate.
This means that all imported goods are 4,24% more expensive than in the base year.
Numeraire of the static model is consumer price index, thus CPI change in all
scenarios equal to zero. Since only relative prices matters in the computable general
equilibrium models, all other prices are quoted in terms of the numeraire (CPI in our case).
Given that CPI is fixed, changes in the exchange rate reflect changes in the real exchange
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 22
rate. In the central scenario wages change by -1,33% and return to mobile capital by -
0,73%.
Return to specific capital in extracting industries or natural rent, decreases for
crude oil production (-3,22%), indicating reduction of production activities.
All other extracting sectors feel much better with increase in return to specific
capital in the Central scenario. The resource rent in production of natural gas rises (4,2%),
as well as the resource rent in production of coal (4,26%), and other mining activities
(5,94%).
Aggregated production index rises by 0,57%. Agriculture production index rises by
0,08%. Extraction production stays constant on the level of the base year. Manufacturing
production index rises by 0,91%, which indicates shift of the resources to manufacturing
sector.
Services production index decreases by -0,42%. This is the consequence of
decline in government spending, since government’s demand drives total demand for
services.
Structural changes induced by deterioration of the terms of trade lead to
reallocation of mobile factors: workers change industries, as well as mobile capital.
Though, the magnitude of reallocation is not significant: 0,66% of mobile capital changes
sectors in the Central scenario, and 1,14% of workers.
5.3. Simulations results: steady-state model
The steady-state model is an extension of the comparative static model. The goal
of the steady-state calculation is to evaluate the upper bound (Rutherford and Tarr 2003)
on welfare changes associated with terms of trade deterioration for the Russian economy.
In the comparative static model the price of capital varies, while total supply of
capital is fixed. In the steady-state model the mobile capital stock and investment demand
are endogenously determined while the price of capital is constant. In other words, the
steady-state model solves for time-invariant capital stock. In the steady-state model
optimal capital stock is such that cost of investment equals the discounted stream of rents
on installed capital7. “This can be viewed as a multi-sector version of the “golden rule”
equilibrium” (Rutherford and Tarr 2003).
7 In the present version of the model depreciation is set to zero.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 23
Major difference between the results of comparative static and steady-state
models is captured in the changes of investment demand. As a result of deterioration of
the terms of trade optimal capital stock for the economy decreases, causing investment
demand to go down even further, then in the comparative static case. There is a -1,56%
decrease in the total investment demand in the Central scenario of the steady-state model
vs. decrease of -0,87% in the comparative static case.
The effects induced by the ToT deterioration on the capital stock echoes in total
production index decreases. Thus, a decrease in the terms of trade pushes economy to
an inferior steady state, characterized by decrease in the welfare of a representative
consumer, lower level of production and consumption.
Overall economic impacts: steady-state model, Central scenario
Overall economic impacts for the Central scenario in the settings of the steady-
state model are shown in the table below (Table 10). The results are presented for the
Central scenario and its components.
Welfare changes associated with the Central scenario indicate a significant
decrease in the welfare of the representative agent up to -2,46% of benchmark
consumption level or -1,29% of the base year GDP. These results exceed welfare
changes in the Central scenario of the static model, and we can refer to these values as
upper bound of possible changes in welfare in the dynamic modelling exercise
(Rutherford and Tarr 2003).
Percentage change of the GDP in the Central scenario of the steady-state model
is of the same magnitude as representative agent’s decrease in welfare in terms of the
benchmark GDP: -2,51%.
The decline in the GDP is driven by decrease in government consumption (-
5,21%). Private consumption decline (-2,46%) as well.
The external closure of the steady-state model is the same as in the static model,
i.e. trade balance is fixed in real terms and the exchange rate adjusts to changes in
relative prices of exported and imported goods. The exchange rate is defined in unites of
local currency to units of foreign currency, thus an increase in the value of the exchange
rate means depreciation of the local (domestic) currency. A decrease in the exchange
rate means that domestic currency strengthens.
The Central scenario of the steady-state model is associated with a 4,3% increase
in the exchange rate. This means that all imported goods are 4,02% more expensive than
in the base year.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 24
Numeraire of the steady-state model is consumer price index, thus CPI change in
all scenarios equals to zero. Since only relative prices matters in the computable general
equilibrium models, all other prices are quoted in terms of the numeraire (CPI in our case).
Given that CPI is fixed, changes in the exchange rate reflect changes in the real exchange
rate.
Representative agent’s income comes from primary factors. In the central scenario
of the steady-state model wages change by -2,6% and return to mobile capital by -0,08%.
Return to specific capital in extracting industries or natural rent, decreases for
crude oil production (-4,02%), indicating reduction of production activities. All other
extracting sectors feel much better with increase in return to specific capital in the Central
scenario: the resource rent in production of natural gas rises (3,24%), as well as the
resource rent in production of coal (3,36%), and other mining activities (5,14%).
Aggregated production index decreases by -0,347%. Agriculture production index
increases insignificantly (by 0,03%), extraction production index decreases by -0,05%,
manufacturing production index rises by 0,73%. This indicates shift of the resources to
manufacturing sector, along the same lines, wish we saw in the static case. Though,
increase in production of manufacturing doesn’t outweigh decrease in all other parts of
the economy, contrary to the result in the static model. Services production index
decreases by -1,05%.
Structural changes induced by deterioration of the terms of trade lead to
reallocation of mobile factors: workers change industries, as well as mobile capital. The
magnitude of reallocation in the steady-state model is more significant than in the static
one: 2% of mobile capital changes sectors in the Central scenario, and 1,2% of workers.
5.4. Changes on the industry level
Output changes
Changes on the industry level are presented in the Appendix (Table 9-Table 11).
On the industry level we can trace the same tendencies that were obvious on the macro
level: decrease in private consumption, decrease in imports, relative increase in exports
and associated with export dynamics changes in production. Exporting becomes a
profitable alternative to stagnating domestic market. Though, this doesn’t lead to an
export-led growth.
Industrial changes in the comparative static (Table 9) and steady-state (Table 11)
models describe similar pictures but have important differences. Industrial output change
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 25
induced by the terms of trade deterioration depend on the cost structure of the industries,
and changes in domestic demand. Magnitude of changes industry output are much bigger
in the steady-state version of the model, and in the static one. Partially this reflects a
much deeper restructuring of the economy under assumption of the steady-state model:
reduction of installed capital, induced by the ToT change, and a much deeper decrease
in imports lead to a bigger reallocation of factors, which was discussed above.
Price changes
Changes in prices on the industry level are presented in the Appendix (Table 13).
Changes in prices of output, industry revenues, costs of manufactured intermediates and
intermediates services in production are presented for the Central scenario of the static
model. As it is evident in case of output changes on the industry level, we can trace the
same tendencies that manifest themselves on the macro level: resulting prices on the
industry level is a result of two main forces, decrease of domestic demand due to
decrease of disposable income of the representative agent and increase in prices due to
depreciation of the national currency.
The propagation of the exchange rate devaluation into production costs goes along
the lines of the structure of the use of imported intermediates, as presented in the figure
below (Figure 6).
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 26
Figure 6. Imports in intermediate consumption: darker cells correspond to higher share of imports in intermediate use by industry and by intermediate commodity group, benchmark dataset, 2011.
Source: author’s calculations based on 2011 Russian input-output tables
From the figure above it is evident, that according to the data in the system of national
accounts, the dependence of the Russian economy on imports is not industry-based, but
can be described as product-based. There is evident tendency of all industries to
consume more imported leather products (s019) and imported office electronics (s30)
then domestic ones. As a consequence, pass through of exchange rate depreciation
associated with terms of trade shock would be more in costs of those industries which
use those intermediate goods relatively more than others.
An evidence of this tendency can be traced in changes of cost indices of production
presented in Appendix (Table 13). Average change in costs of intermediates across all
industries is 0.21. Imported services are almost absent from the intermediate
consumption, there is no influence of exchange rate deterioration on the cost of
intermediate services. So, a 4,3% increase in the real8 exchange rate corresponds to
average increase of 0,2% in cost index of intermediate goods consumption.
8 Please note, that CPI is fixed as a numeraire in the Central scenario of the static model, thus real and nominal values of the exchange rate coincide.
s01 s02 s05 s10 oil gas s112 s12x s15 s15x s16 s17 s18 s19 s20 s21 s22 s23 s24 s25 s26 s27 s28 s29 s30 s31 s32 s33 s34 s35 s36x s40 s41 s45 trd s55 trn s63 s64 s65x s70 s71 s72 s73 s74 s75 s80 s85 s90 s91 s92 s93x
s01 0 ,0 0 ,5 0 ,1 0 ,0 0 ,0 0 ,1 1 ,0 0 ,8 0 ,2 0 ,2 0 ,3 0 ,1 0 ,1 0 ,2 1 ,0 0 ,0 0 ,2 0 ,3 0 ,1 0 ,1 0 ,3 0 ,2 0 ,2 0 ,1 0 ,3 0 ,1 0 ,2 0 ,3 0 ,5 0 ,1 0 ,1 0 ,0 0 ,0 0 ,2 0 ,2 0 ,4 0 ,4 0 ,4 0 ,4 0 ,2 0 ,5
s02 0 ,0 0 ,0 0 ,0 1 ,0 0 ,0 0 ,0 0 ,6 0 ,2 0 ,0 0 ,3 0 ,0 0 ,5 0 ,7 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,1 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,2 0 ,1 0 ,2
s05 0 ,3 0 ,1 0 ,2 0 ,2 0 ,1 0 ,0 0 ,2 0 ,2 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,0 0 ,2 0 ,2 0 ,1 0 ,2
s10 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,2 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1
oil 0 ,0
gas 0 ,0
s112 0 ,1 0 ,2
s12x 0 ,2 0 ,1 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,3 0 ,2 0 ,1 0 ,3 0 ,4 0 ,1 0 ,2 0 ,1 0 ,1 0 ,0 0 ,1 0 ,2 0 ,1 0 ,2 0 ,2 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,2 0 ,2 0 ,1 0 ,1 0 ,5 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,3 0 ,2 0 ,1 0 ,1 0 ,0
s15 0 ,1 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,4 0 ,3 0 ,2 0 ,1 0 ,1 0 ,2 0 ,1 0 ,3 0 ,3 0 ,4 0 ,3 0 ,2 0 ,3 0 ,2 0 ,4 0 ,2 0 ,3 0 ,2 0 ,3 0 ,3 0 ,2 0 ,6 0 ,2 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,1 0 ,1 0 ,3 0 ,2 0 ,3 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,3
s15x 0 ,3 0 ,0 0 ,1 0 ,2 0 ,2 0 ,0 0 ,3 0 ,0 0 ,1 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,0 0 ,1 0 ,2 0 ,1 0 ,0 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1
s16 0 ,6 0 ,0 0 ,0 0 ,0
s17 0 ,3 0 ,4 0 ,3 0 ,4 0 ,5 0 ,5 0 ,4 0 ,5 0 ,5 0 ,5 0 ,3 0 ,6 0 ,6 0 ,5 0 ,5 0 ,5 0 ,6 0 ,3 0 ,4 0 ,5 0 ,6 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,6 0 ,4 0 ,5 0 ,5 0 ,5 0 ,5 0 ,3 0 ,5 0 ,5 0 ,5 0 ,4 0 ,4 0 ,5 0 ,6 0 ,4 0 ,5 0 ,6 0 ,5 0 ,6 0 ,5 0 ,4 0 ,6 0 ,3 0 ,5 0 ,5
s18 0 ,4 0 ,1 0 ,4 0 ,4 0 ,2 0 ,1 0 ,2 0 ,1 0 ,5 0 ,4 0 ,0 0 ,4 0 ,4 0 ,6 0 ,1 0 ,2 0 ,4 0 ,1 0 ,6 0 ,7 0 ,4 0 ,3 0 ,4 0 ,6 0 ,1 0 ,5 0 ,3 0 ,5 0 ,6 0 ,4 0 ,2 0 ,7 0 ,7 0 ,1 0 ,6 0 ,8 0 ,7 0 ,6 0 ,4 0 ,4 0 ,6 0 ,7 0 ,8 0 ,7 0 ,4 0 ,5 0 ,8 0 ,8 0 ,2 0 ,8 0 ,8 0 ,5
s19 0 ,8 1 ,0 0 ,8 0 ,9 0 ,9 1 ,0 0 ,8 0 ,9 0 ,9 0 ,8 0 ,3 0 ,2 0 ,5 1 ,0 0 ,9 0 ,2 0 ,9 0 ,9 0 ,5 0 ,9 0 ,9 0 ,8 0 ,9 1 ,0 0 ,6 0 ,4 0 ,9 0 ,5 0 ,2 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,8 0 ,8 1 ,0 0 ,9 0 ,9 0 ,8 0 ,9 0 ,9 0 ,8 0 ,9 0 ,9 0 ,9
s20 0 ,0 0 ,0 0 ,1 0 ,1 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,1 0 ,3 0 ,3 0 ,1 0 ,1 0 ,0 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,1 0 ,2 0 ,1 0 ,2 0 ,0 0 ,0 0 ,0 0 ,8 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,1 0 ,2 0 ,2 0 ,6
s21 0 ,1 0 ,1 0 ,2 0 ,1 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,3 0 ,1 0 ,2 0 ,1 0 ,1 0 ,8 0 ,2 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,5 0 ,1 0 ,3 0 ,3 0 ,1 0 ,1 0 ,1 0 ,6 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,2 0 ,2 0 ,1 0 ,1 0 ,2 0 ,1
s22 0 ,0 0 ,1 0 ,2 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,2 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,0 0 ,0 0 ,2 0 ,1 0 ,2 0 ,1 0 ,1 0 ,0 0 ,0 0 ,2 0 ,1 0 ,1 0 ,4 0 ,1 0 ,1 0 ,0 0 ,1 0 ,0
s23 0 ,0 0 ,0 0 ,1 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,2 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0
s24 0 ,2 0 ,4 0 ,3 0 ,3 0 ,4 0 ,4 0 ,4 0 ,3 0 ,5 0 ,5 0 ,7 0 ,5 0 ,6 0 ,5 0 ,4 0 ,5 0 ,6 0 ,3 0 ,4 0 ,4 0 ,3 0 ,3 0 ,4 0 ,4 0 ,4 0 ,4 0 ,3 0 ,4 0 ,4 0 ,3 0 ,4 0 ,4 0 ,4 0 ,5 0 ,4 0 ,4 0 ,4 0 ,4 0 ,3 0 ,5 0 ,4 0 ,5 0 ,3 0 ,4 0 ,5 0 ,6 0 ,4 0 ,7 0 ,2 0 ,5 0 ,4 0 ,4
s25 0 ,4 0 ,5 0 ,4 0 ,5 0 ,4 0 ,4 0 ,4 0 ,5 0 ,3 0 ,2 0 ,3 0 ,3 0 ,3 0 ,4 0 ,4 0 ,3 0 ,3 0 ,3 0 ,3 0 ,5 0 ,3 0 ,4 0 ,3 0 ,4 0 ,4 0 ,4 0 ,4 0 ,4 0 ,5 0 ,4 0 ,4 0 ,4 0 ,4 0 ,3 0 ,3 0 ,5 0 ,5 0 ,4 0 ,3 0 ,5 0 ,2 0 ,4 0 ,4 0 ,4 0 ,4 0 ,4 0 ,3 0 ,5 0 ,4 0 ,4 0 ,4 0 ,4
s26 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,4 0 ,2 0 ,1 0 ,1 0 ,2 0 ,1 0 ,2 0 ,1 0 ,1 0 ,2 0 ,1 0 ,2 0 ,2 0 ,2 0 ,1 0 ,3 0 ,6 0 ,2 0 ,2 0 ,1 0 ,0 0 ,1 0 ,1 0 ,3 0 ,0 0 ,0 0 ,1 0 ,6 0 ,1 0 ,0 0 ,2 0 ,2 0 ,1 0 ,1 0 ,2 0 ,1 0 ,0 0 ,1 0 ,2 0 ,2
s27 0 ,1 0 ,1 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,1 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,2 0 ,1 0 ,2 0 ,2
s28 0 ,5 0 ,5 0 ,5 0 ,5 0 ,4 0 ,5 0 ,6 0 ,5 0 ,3 0 ,3 0 ,3 0 ,6 0 ,3 0 ,3 0 ,6 0 ,2 0 ,6 0 ,2 0 ,3 0 ,6 0 ,3 0 ,4 0 ,2 0 ,2 0 ,3 0 ,3 0 ,3 0 ,3 0 ,3 0 ,2 0 ,7 0 ,1 0 ,4 0 ,3 0 ,3 0 ,6 0 ,2 0 ,4 0 ,5 0 ,6 0 ,4 0 ,2 0 ,7 0 ,3 0 ,3 0 ,4 0 ,5 0 ,6 0 ,5 0 ,3 0 ,6 0 ,6
s29 0 ,4 0 ,3 0 ,2 0 ,2 0 ,2 0 ,3 0 ,1 0 ,2 0 ,3 0 ,3 0 ,5 0 ,6 0 ,6 0 ,6 0 ,4 0 ,4 0 ,2 0 ,3 0 ,2 0 ,3 0 ,3 0 ,2 0 ,4 0 ,5 0 ,3 0 ,4 0 ,2 0 ,5 0 ,6 0 ,5 0 ,3 0 ,3 0 ,3 0 ,4 0 ,4 0 ,3 0 ,3 0 ,3 0 ,1 0 ,7 0 ,2 0 ,4 0 ,5 0 ,4 0 ,4 0 ,1 0 ,2 0 ,2 0 ,2 0 ,5 0 ,2 0 ,6
s30 0 ,9 0 ,9 0 ,9 0 ,8 0 ,8 0 ,8 0 ,9 0 ,9 0 ,9 0 ,9 0 ,5 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,8 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,8 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,8 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,9 0 ,8 0 ,9 0 ,9 0 ,9 0 ,8 0 ,8
s31 0 ,5 0 ,4 0 ,5 0 ,5 0 ,3 0 ,4 0 ,2 0 ,4 0 ,4 0 ,5 0 ,4 0 ,4 0 ,5 0 ,4 0 ,3 0 ,4 0 ,4 0 ,2 0 ,4 0 ,6 0 ,4 0 ,4 0 ,5 0 ,5 0 ,4 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,3 0 ,4 0 ,4 0 ,5 0 ,5 0 ,4 0 ,4 0 ,3 0 ,2 0 ,3 0 ,4 0 ,3 0 ,5 0 ,4 0 ,5 0 ,5 0 ,5 0 ,5 0 ,4 0 ,5 0 ,4
s32 0 ,1 0 ,4 0 ,3 0 ,7 0 ,5 0 ,5 0 ,6 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,5 0 ,4 0 ,1 0 ,3 0 ,5 0 ,4 0 ,5 0 ,5 0 ,5 0 ,7 0 ,5 0 ,8 0 ,6 0 ,5 0 ,5 0 ,5 0 ,7 0 ,6 0 ,3 0 ,5 0 ,6 0 ,7 0 ,5 0 ,3 0 ,6 0 ,5 0 ,6 0 ,5 0 ,6 0 ,3 0 ,3 0 ,5 0 ,4 0 ,3 0 ,4
s33 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,3 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,3 0 ,2 0 ,6 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,1 0 ,2 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,3 0 ,6 0 ,1 0 ,1 0 ,3 0 ,1
s34 0 ,6 0 ,6 0 ,6 0 ,5 0 ,6 0 ,6 0 ,6 0 ,6 0 ,5 0 ,4 0 ,6 0 ,6 0 ,7 0 ,5 0 ,6 0 ,6 0 ,6 0 ,5 0 ,6 0 ,6 0 ,6 0 ,5 0 ,3 0 ,6 0 ,1 0 ,3 0 ,6 0 ,3 0 ,6 0 ,6 0 ,6 0 ,6 0 ,5 0 ,6 0 ,6 0 ,6 0 ,6 0 ,6 0 ,5 0 ,6 0 ,6 0 ,5 0 ,6 0 ,6 0 ,6 0 ,6 0 ,6 0 ,5 0 ,6 0 ,6
s35 0 ,3 0 ,1 0 ,0 0 ,1 0 ,0 0 ,0 0 ,1 0 ,0 0 ,1 0 ,6 0 ,1 0 ,0 0 ,5 0 ,1 0 ,1 0 ,0 0 ,2 0 ,2 0 ,1 0 ,1 0 ,0 0 ,2 0 ,3 0 ,1 0 ,4 0 ,1 0 ,2 0 ,2 0 ,1 0 ,0 0 ,3 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,6 0 ,2 0 ,1 0 ,1 0 ,6
s36x 0 ,2 0 ,1 0 ,7 0 ,2 0 ,3 0 ,1 0 ,2 0 ,1 0 ,3 0 ,3 0 ,6 0 ,2 0 ,7 0 ,6 0 ,3 0 ,0 0 ,3 0 ,4 0 ,2 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,3 0 ,2 0 ,3 0 ,1 0 ,8 0 ,1 0 ,1 0 ,2 0 ,2 0 ,3 0 ,1 0 ,2 0 ,1 0 ,2 0 ,1 0 ,3 0 ,1 0 ,3 0 ,7 0 ,1 0 ,3 0 ,5 0 ,4 0 ,4 0 ,6 0 ,6 0 ,6 0 ,4
s40 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0
s41 0 ,0
s45 0 ,0 0 ,0 0 ,1 0 ,1 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,1
trd 0 ,1
s55 0 ,1
trn 0 ,0 0 ,1 0 ,5 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,0 0 ,1 0 ,1 0 ,2 0 ,0 0 ,1 0 ,1 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,2 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,1 0 ,2 0 ,2 0 ,0 0 ,0 0 ,1 0 ,3 0 ,1 0 ,2 0 ,1 0 ,1 0 ,0 0 ,1 0 ,2 0 ,0
s63 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,2 0 ,0 0 ,0
s64 0 ,2 0 ,1
s65x 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,1 0 ,1 0 ,1 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,0 0 ,1 0 ,1 0 ,0 0 ,1 0 ,0
s70 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0
s71 0 ,0 0 ,8 0 ,1 0 ,1 0 ,1 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,3 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,3 0 ,0
s72 0 ,0 0 ,0 0 ,0 0 ,0 0 ,2 0 ,2 0 ,3 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0 0 ,1 0 ,1 0 ,2 0 ,0 0 ,0 0 ,1 0 ,1 0 ,0 0 ,1 0 ,0 0 ,0 0 ,1 0 ,2 0 ,0 0 ,0 0 ,3 0 ,1 0 ,1 0 ,2 0 ,3 0 ,0 0 ,0 0 ,1 0 ,0 0 ,0
s74 0 ,1 0 ,1 0 ,0 0 ,2 0 ,2 0 ,0 0 ,0 0 ,1 0 ,1 0 ,1 0 ,3 0 ,2 0 ,4 0 ,3 0 ,2 0 ,2 0 ,3 0 ,3 0 ,2 0 ,3 0 ,2 0 ,2 0 ,3 0 ,2 0 ,4 0 ,3 0 ,2 0 ,3 0 ,2 0 ,2 0 ,3 0 ,2 0 ,0 0 ,3 0 ,2 0 ,3 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,1 0 ,3 0 ,4 0 ,2 0 ,3 0 ,3 0 ,2 0 ,0 0 ,1 0 ,3 0 ,1
s90 0 ,1 0 ,0
s92 0 ,4 0 ,5 0 ,2 0 ,5 0 ,5 0 ,2 0 ,5 0 ,5 0 ,4 0 ,1 0 ,5 0 ,5 0 ,3 0 ,5 0 ,5 0 ,3 0 ,4 0 ,5 0 ,1 0 ,2 0 ,0 0 ,1 0 ,4 0 ,5 0 ,2 0 ,4 0 ,0 0 ,2 0 ,2 0 ,3 0 ,5 0 ,3 0 ,5 0 ,0 0 ,1 0 ,1 0 ,0 0 ,0 0 ,5 0 ,0 0 ,1
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 27
5.5. Validation of the model: historical simulations
Validation of computable general equilibrium model is important and time-
consuming process. There are different ways to assure validity of a computational
models, and a CGE in particular. A computational model (Dixon and Rimmer 2013):
(i) should be computationally sound. Computational quality of the present
model is ensured by numerous checks, including replication of the
benchmark dataset.
(ii) should use accurate up-to-date data. As discussed earlier, the most up-
to-date available data is used for the creation of the benchmark dataset.
(iii) should adequately captures behavioural and institutional characteristics of
the relevant part of the economy. A range of behavioural and institutional
characteristics is used in the presented model based on the latest
research on Russian economy.
(iv) should be consistent with history. In order to validate model’s consistency
historical experiments were conducted. The setting of the experiments
and results are discussed below.
A historical scenario is defined as changes in exogenous parameters of the model
that were observed in the data. Validation of the model is done on the basis of goodness
of fit of the detailed results to the historical values of endogenous variables of the model.
One of many possible measures of the goodness of fit is the “average error”
measure proposed by (Dixon and Rimmer 2013):
Where fc - model forecast of the percentage change in the output of goods c;
ac — statistics on change in output;
N - the number of product groups in the model.
As a benchmark value for the average error of a detailed industrial historical
scenario results (Dixon and Rimmer 2013) used average error calculated for the USAGE
model, a detailed computable general equilibrium model for the American economy9.
Benchmark value equals AE = 19% (Dixon and Rimmer 2013).
9 Detailed description of the USAGE model is available at https://www.copsmodels.com/usage.htm
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 28
The most important element of the historical simulation is correct assessment of
changes in exogenous parameters of the model. In our case the most important
exogenous parameters are world prices of exports and imports. The importance of these
parameters for validation of the present model is based on the primary use of the model
in estimation of the effect of the change in terms of trade for the Russian economy.
In order to calculate changes in export and import prices on the level of commodity
groups, presented in the model, several datasets were used:
1) CEPII TUV dataset (Gaulier et al. 2010);
2) UN COMTRADE;
3) EAEU detailed trade data on 10-digit HS code level;
4) IMF Commodity price database;
5) IMF Commodity Terms of Trade (Gruss and Kebhaj 2019);
6) CBR database of main export prices of Russian exports.
Price data for exports and imports is highly volatile, and the most time-consuming
effort is to exclude outliers from the data. The results of this process for the export price
data are presented in table below (Table 3). Changes in import prices are presented in
the Appendix (Table 7-Table 8).
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 29
Table 3. Changes in export prices to 2011 by commodity group
Source: author’s estimates, UN COMTRADE, CEPII TUV databases
One of important characteristics of the historical response of the Russian economy
on the changes in terms of trade that occurred in 2014-2015 was stable real output of
the extraction sector. As we saw earlier this contradicts predictions of both static and
steady-state models.
The simulations results presented in the table below (Table 4) suggest that behaviour
of Russian oil and gas extraction sector is explained by changes in export taxes, which
were almost cut by half at the same time when world prices fall, thus leaving the perceived
dollar price of oil exports for firms in the industry almost unchanged. This situation is
depicted in scenario #4. In a medium term time span, mimicked by 30% of all capital in
the economy being specific, difference between model’s forecast of output of oil and gas
2012 2013 2014 2015 2016
01 Agriculture 101% 143% -11% -22% -36%
02 Forestry -2% 1% -2% -19% -24%
05 Fishing 29% 49% 80% 84% 80%
10 Mining of coal -5% -19% -27% -41% -50%
11101 Crude petroleum 5% 2% -5% -50% -61%
11102 Natural gas 18% 10% 32% 9% -35%
12 Mining of metal ores 50% 35% 38% 35% 26%
15 Food 54% 48% 42% 19% 18%
15 -9 Beverages 19% 14% 10% -19% -21%
16 Tobacco products 40% 45% 55% 39% 16%
17 Textiles 66% 62% 53% 32% 23%
18 Wearing apparel 19% 72% -75% -90% -91%
19 Leather 49% 59% 65% 20% 23%
20 Wood products 3% 6% 35% -24% -19%
21 Paper products 55% 49% 52% 17% 8%
22 Publishing 93% 59% 100% 46% 39%
23 Refined petroleum 14% -74% -74% -78% -77%
24 Chemicals -10% -10% -13% -20% -95%
25 Plastic products 24% 7% -11% -29% -31%
26 Non-metallic products 40% 37% 66% 3% -6%
27 Basic metals 16% 7% 0% -19% -17%
Change in export prices to 2011
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 30
sector and historical values, reported by Rosstat, equal to 0,4%. Further alternation of the
model, including changes in the import prices, distort the results.
Table 4. Design and results of historical simulations.
The results of the historical scenarios suggest that the presented computable
general equilibrium model is valid for use of scenario estimation for the Russian economy.
It could picture adequately diverse industrial response on terms of trade shocks.
Historical scenarios stress importance of fiscal changes in estimating changes in
industry output at the time of terms of trade shocks, especially changes in export taxes in
extraction industries.
#1 #2 #3 #4 #5 #6 #7 #8
Scenario design
Change in export prices * * * * * * * *
Change in import prices * * *
Change in export taxes * * * * * * *
Share of specific capital in all
industries0 0 0 30% 30% 50% 50% 50%
Share of specific capital in
extraction30% 30% 30% 30% 60% 50% 30% 70%
GTAP elasticities * *
Average error
AE 17,6 19,8 20,0 16,4 20,3 17,3 17,3 20,4
Oil and gas output indicator
Real output (% difference,
model to statistics) -1,98 0,53 -7,09 0,40 -4,96 -1,90 -1,90 -2,60
Source: Author's calculations
Model validation scenarios
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 31
6. Conclusion
This article examines the impact of changes in world prices on the Russian
economy. In particular, I am interested in the change in production as a result of changes
in world prices for the main Russian export and import commodities.
A number of recent macro studies ((Atalay 2017), (Acemoglu, Ozdaglar, and
Tahbaz-salehi 2017) (Burstein, Kurz, and Tesar 2008)) stressed importance of explicit
introduction of the intermediates in the models assessing effects of external shocks,
which is a well-established practice in the computable general equilibrium methodology.
Models of this class permit introduction of rich details and complex production structures
as well as optimizing behaviour of economic agents.
The model presented in the paper belongs to the class of computable general
equilibrium (CGE) models, it has a detailed industry structure, which allows tracing the
effect of changes in world prices on all aspects of the Russian economy.
The results suggest a decrease of welfare of the representative consumer and real
GDP with the deterioration of the terms of trade. In the Central scenario (a 10% decrease
in the world price of crude oil, a 3% decrease in the world price of natural gas and an 8%
decrease in the world price of petroleum products) welfare of the representative
consumer decreases by -1,17% of benchmark consumption level or 0,58% of the base
year GDP in the comparative static model. Percentage change of the GDP in the Central
scenario of the comparative static model is of the same magnitude as representative
agent’s decrease in welfare in terms of the benchmark GDP: -1,55%.
Welfare changes associated with the Central scenario of the steady-state model
indicate a significant decrease in the welfare of the representative agent up to -2,64% of
benchmark consumption level or -1,23% of the base year GDP. Percentage change of
the GDP in the Central scenario of the steady-state model exceeds representative agent’s
decrease in welfare in terms of the benchmark GDP: -2,51%. The GDP response in the
steady-state model is in line with estimates obtained in compatible work (Полбин 2017).
These results exceed welfare changes in the Central scenario of the static model,
and we can refer to these values as upper bound of possible changes in welfare in the
dynamic modelling exercise (Rutherford and Tarr 2003).
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 32
References
Acemoglu, By Daron, Asuman Ozdaglar, and Alireza Tahbaz-salehi. 2017. “Microeconomic Origins of Macroeconomic Tail Risks.” American Economic Review 107 (1): 54–108. https://doi.org/doi.org/10.1257/aer.20151086.
Aghion, Philippe, Philippe Bacchetta, and Abhijit Banerjee. 2000. “A Simple Model of Monetary Policy and Currency Crises.” European Economic Review 44 (4–6): 728–38. https://doi.org/10.1016/S0014-2921(99)00053-7.
Aguiar, Angel, Badri Narayanan, and Robert McDougall. 2016. “An Overview of the GTAP 9 Data Base.” Journal of Global Economic Analysis 1 (1): 181–208. https://doi.org/10.21642/jgea.010103af.
Alekseev, Alexander, Denis Sokolov, Natalia Turdyeva, and Ksenia Yudaeva. 2004. “Estimating the Effects of EU Enlargement, WTO Accession and Formation of FTA with EU or CIS on Russian Economy.” https://www.gtap.agecon.purdue.edu/resources/res_display.asp?RecordID=1485.
Alekseev, Alexander, Natalia Turdyeva, and Ksenia Yudaeva. 2003. “Estimation of the Russia ’ s Trade Policy Options with the Help of the Computable General Equilibrium Model . 1.” Moscow.
Armington, Paul S. 1969. “A Theory of Demand for Products Distinguished by Place of Production.” Edited by I M F Workingpaper. Staff Papers International Monetary Fund 16 (1): 159–78. https://doi.org/10.2307/3866403.
Arrow, K. J., H. B. Chenery, B. S. Minhas, and R. M. Solow. 1961. “Capital-Labor Substitution and Economic Efficiency.” The Review of Economics and Statistics 43 (3): 225–50.
Atalay, Enghin. 2017. “How Important Are Sectoral Shocks?” Online Appendix. Vol. 9. https://doi.org/10.1257/mac.20160353.
Baqaee, David Rezza, and Emmanuel Farhi. 2019. “Productivity and Misallocation in General Equilibrium.” https://doi.org/10.3386/w24007.
Besstremyannaya, G.E., and A.R. Bakhtizin. 2006. “TAX POLICY MEASURES FOR EDUCATION AND HEALTHCARE SECTORS OF RUSSIAN ECONOMY: COMPUTABLE GENERAL EQUILIBRIUM ANALYSIS.” 208. Препринт ЦЭМИ РАН. Москва. sp.lan.cemi-ras.ru/pub/Working_Papers/WP-208.pdf.
Böhringer, Christoph, Thomas F. Rutherford, David G. Tarr, and Natalia Turdyeva. 2015. “Market Structure and the Environmental Implications of Trade Liberalization: Russia’s Accession to the World Trade Organization.” Review of International Economics 23 (5): 897–923. https://doi.org/10.1111/roie.12197.
Burstein, Ariel, Christopher Kurz, and Linda Tesar. 2008. “Trade, Production Sharing, and the International Transmission of Business Cycles.” 13731. NBER Workign Paper Series. NBER Working Paper Series. https://doi.org/10.1016/j.jmoneco.2008.03.004.
Bussolo, Maurizio, and Patrizia Luongo. 2017. “The Distributive Impact of Terms of Trade Shocks.” Policy Research Working Paper, no. February: 1–35.
Cavalcanti, Tiago V. De V., Kamiar Mohaddes, and Mehdi Raissi. 2015. “Commodity Price Volatility And The Sources Of Growth.” Journal of Applied Econometrics 30 (6): 857–73. https://doi.org/10.1002/jae.
Devarajan, Shantayanan, and Sherman Robinson. 2013. Contribution of Computable General Equilibrium Modeling to Policy Formulation in Developing Countries. Handbook of Computable General Equilibrium Modeling. Vol. 1. Elsevier. https://doi.org/10.1016/B978-0-444-59568-3.00005-5.
Dixon, Peter B., Robert B. Koopman, and Maureen T. Rimmer. 2013. “The MONASH Style of Computable General Equilibrium Modeling: A Framework for Practical
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 33
Policy Analysis.” In Handbook of Computable General Equilibrium Modeling, Volume 1:23–103. https://doi.org/http://dx.doi.org/10.1016/B978-0-444-59568-3.00002-X.
Dixon, Peter B., and Maureen T. Rimmer. 2013. Validation in Computable General Equilibrium Modeling. Handbook of Computable General Equilibrium Modeling. Vol. 1. Elsevier. https://doi.org/10.1016/B978-0-444-59568-3.00019-5.
———. 2016. “Johansen’s Legacy to CGE Modelling: Originator and Guiding Light for 50 Years.” Journal of Policy Modeling 38 (3): 421–35. https://doi.org/10.1016/j.jpolmod.2016.02.009.
Dong, Baomin, Xili Ma, Ningjing Wang, and Weixian Wei. 2017. “Impacts of Exchange Rate Volatility and International Oil Price Shock on China’s Regional Economy: A Dynamic CGE Analysis.” Energy Economics. https://doi.org/10.1016/j.eneco.2017.09.014.
Easterly, Wiiliam, Robert King, Ross Levine, and Sergio Rebelo. 1994. “Policy, Technology Adoption and Growth.” Centre for Economic Policy Research Discussion Paper 957 (March): 15. https://doi.org/10.3386/w4681.
Fehr, Hans. 2016. “CGE Modeling Social Security Reforms.” Journal of Policy Modeling 38 (3): 475–94. https://doi.org/10.1016/j.jpolmod.2016.02.007.
Fehr, Hans, Sabine Jokisch, Manuel Kallweit, Fabian Kindermann, and Laurence J. Kotlikoff. 2013. “Generational Policy and Aging in Closed and Open Dynamic General Equilibrium Models.” In Handbook of Computable General Equilibrium Modeling, 1:1719–1800. https://doi.org/10.1016/B978-0-444-59568-3.00027-4.
Gatti, Domenico Delli, Mauro Gallegati, Bruce C Greenwald, and Joseph E Stiglitz. 2007. “Net Worth, Exchange Rates, and Monetary Policy: The Effects of a Devaluation in a Financially Fragile Environment.” 13244. NBER Working Paper Series. NBER Working Paper Series.
Gaulier, Guillaume, Julien Martin, Isabelle Méjean, and Soledad Zignago. 2010. “International Trade Price Indices.” 2010–23. CEPII Working Paper.
Giesecke, James A, and John R Madden. 2013. Chapter 7 - Regional Computable General Equilibrium Modeling. Handbook of Computable General Equilibrium Modeling. Vol. Volume 1. Elsevier. https://doi.org/http://dx.doi.org/10.1016/B978-0-444-59568-3.00007-9.
Greenwald, Bruce C., and Joseph E. Stiglitz. 1993. “Financial Market Imperfections and Business Cycles.” The Quarterly Journal of Ecoomics 108 (1): 77–114. http://www.jstor.org/stable/2118496.
Gruss, Bertrand, and Suhaib Kebhaj. 2019. “Commodity Terms of Trade : A New Database.” IMF Working Paper.
Gylfason, T., and M. Schmid. 1983. “Does Devaluation Cause Stagflation?” University of Stockholm, Institute for International Economic Studies, Reprint Series 224 (4): 641–54. https://doi.org/10.2307/135045.
Helm, Carsten, and Thomas F. Rutherford. 2004. “Self-Enforcing Agreements and
International Trade in Greenhouse Gas Emission Rights ∗ Self-Enforcing Agreements and International Trade In.” Environmental and Resource Economics, no. 919.
Hertel, Thomas. 2013. “Global Applied General Equilibrium Analysis Using the Global Trade Analysis Project Framework.” In Handbook of Computable General Equilibrium Modeling, edited by Kenneth J. Arrow and Michael D. Intriligator, 1:815–76. Handbook of Computable General Equilibrium Modeling. Elsevier. https://doi.org/10.1016/B978-0-444-59568-3.00012-2.
Holmøy, Erling, and Birger Strøm. 2013. Chapter 3 - Computable General Equilibrium Assessments of Fiscal Sustainability in Norway. Handbook of Computable General Equilibrium Modeling SET, Vols. 1A and 1B. Vol. Volume 1.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 34
https://doi.org/http://dx.doi.org/10.1016/B978-0-444-59568-3.00003-1. Horridge, Mark, Alex Meeraus, Ken Pearson, and Thomas F. Rutherford. 2013.
Handbook of Computable General Equilibrium Modeling SET, Vols. 1A and 1B. Handbook of Computable General Equilibrium Modeling. Vol. 1. Elsevier. https://doi.org/10.1016/B978-0-444-59568-3.00020-1.
IMF. 2017. Russian Federation. International Monetary Fund. 2017. World Economic Outlook: Gaining Momentum?
World Economic Outlook April 2017. Washington. www.imfbookstore.org. Jensen, Jesper, Thomas F. Rutherford, and David G. Tarr. 2004. “The Impact of
Liberalizing Barriers to Foreign Direct Investment in Services: The Case of Russian Accession to the World Trade Organization.” WPS3391. World Bank Policy Research. https://doi.org/10.1017/CBO9781107415324.004.
Kolik, Alexander, Artur Radziwill, and Natalia Turdyeva. 2015. “Improving Transport Infrastructure in Russia.” 1193. OECD Economics Department Working Papers. ECONOMICS DEPARTMENT WORKING PAPERS. Paris. http://dx.doi.org/10.1787/5js4hmcs3mxp-en.
Kose, M.Ayhan. 2002. “Explaining Business Cycles in Small Open Economies.” Journal of International Economics 56 (2): 299–327. https://doi.org/10.1016/S0022-1996(01)00120-9.
Lofgren, Hans, Marcelle Thomas, and Moataz El-said. 2002. A Standard Computable General Equilibrium (CGE) Model in GAMS. Microcomputers in Policy Research. Washington: International Food Policy Research Institute.
Mathiesen, Lars. 1985. “Computation of Economic Equilibria by a Sequence of Linear Complementarity Problems.” Mathematical Programming Study 23: 144–62.
Mendoza, Enrique. 1995. “The Terms of Trade, the Real Exchange Rate, and Economic Fluctuations.” International Economic Review. https://doi.org/10.2307/2527429.
Nick, Sebastian, and Stefan Thoenes. 2014. “What Drives Natural Gas Prices? - A Structural VAR Approach.” Energy Economics 45 (January 2009): 517–27. https://doi.org/10.1016/j.eneco.2014.08.010.
Polanco Martínez, Josué M., Luis M. Abadie, and J. Fernández-Macho. 2018. “A Multi-Resolution and Multivariate Analysis of the Dynamic Relationships between Crude Oil and Petroleum-Product Prices.” Applied Energy 228 (July): 1550–60. https://doi.org/10.1016/j.apenergy.2018.07.021.
Pyatt, Graham. 1991. “Fundamentals of Social Accounting.” Economic Systems Research 3 (3): 315–41. https://doi.org/10.1080/09535319100000024.
Pyatt, Graham, and Jeffery I. Round. 1985. Social Accounting Matrices: A Basis for Planning. Edited by Graham Pyatt and Jeffery I. Round. Washington D.C.: The World Bank. https://doi.org/10.4324/9781315301112-1.
Ramberg, David J., Y. H. Henry Chen, Sergey Paltsev, and John E. Parsons. 2017. “The Economic Viability of Gas-to-Liquids Technology and the Crude Oil–Natural Gas Price Relationship.” Energy Economics 63: 13–21. https://doi.org/10.1016/j.eneco.2017.01.017.
Reinsdorf, M. B. 2010. “Terms of Trade Effects: Theory and Measurement.” Review of Income and Wealth 56 (1): S177–205. https://doi.org/10.1111/j.1475-4991.2010.00384.x.
Rose, Adam, and Shu-Yi Liao. 2005. “Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions*.” Journal of Regional Science 45 (1): 75–112. https://doi.org/10.1111/j.0022-4146.2005.00365.x.
Rutherford, Thomas F., and Sergey Paltsev. 1999. “From an Input-Output Table to a General Equilibrium Model : Assessing the Excess Burden of Indirect Taxes in Russia.” Department of Economics, University of Colorado.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 35
Rutherford, Thomas F., and David G. Tarr. 2004. “Algebraic Formulation of Services Libearlization Models,” no. 1: 1–23. http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTPROGRAMS/EXTTRADERESEARCH/0,,contentMDK:20273889~menuPK:544862~pagePK:64168182~piPK:64168060~theSitePK:544849~isCURL:Y~isCURL:Y~isCURL:Y~isCURL:Y,00.html.
Rutherford, Thomas F, and David G Tarr. 2003. “Regional Trading Arrangements For Chile : Do The Results Differ With A Dynamic Model?” Economie Internationale 95: 261–82.
Schmitt-Grohé, Stephanie, and Martín Uribe. 2018. “How Important Are Terms-of-Trade Shocks?” International Economic Review 59 (1): 85–111. https://doi.org/10.1111/iere.12263.
Shibusawa, Hiroyuki, Yuzuru Miyata, Hiroyuki Shibusawa, and Yuzuru Miyata. 2011. “EVALUATING THE DYNAMIC AND SPATIAL ECONOMIC IMPACTS OF AN EARTHQUAKE: A CGE APPLICATION TO JAPAN.” Regional Science Inquiry III (2): 13–25.
Tarr, David. 2006. “Regional Impacts of Russia ’ s Accession to the WTO by and Regional Impacts of Russia ’ s Accession to the WTO by Thomas Rutherford and David Tarr.”
Tarr, David G., and Thomas F. Rutherford. 2004. “Poverty Effects of Russia’ s WTO Accession : Modeling ‘Real’ Households and Endogenous Productivity Effects.” Policy.
Tarr, David G., Oleksandr Shepotylo, and Timour Kouduyarov. 2005. “The Structure of Import Tariffs in Russia: 2001-2003.” International Relations, 2001–3.
Timilsina, Govinda R. 2015. Oil Prices and the Global Economy: A General Equilibrium Analysis. Energy Economics. Vol. 49. Elsevier B.V. https://doi.org/10.1016/j.eneco.2015.03.005.
Tokarick, Stephen. 2014. “A Method for Calculating Export Supply and Import Demand Elasticities.” Journal of International Trade and Economic Development 23 (7): 1059–87. https://doi.org/10.1080/09638199.2014.920403.
World Bank Group. 2015. Russia Economic Report: Balancing Economic Adjustment and Transformation. World Bank Group. Vol. 34.
Zhang, Dayong, and Qiang Ji. 2018. “Further Evidence on the Debate of Oil-Gas Price Decoupling: A Long Memory Approach.” Energy Policy 113 (August 2017): 68–75. https://doi.org/10.1016/j.enpol.2017.10.046.
Zodrow, George R, and John W Diamond. 2013. Chapter 11 – Dynamic Overlapping Generations Computable General Equilibrium Models and the Analysis of Tax Policy: The Diamond–Zodrow Model. Handbook of Computable General Equilibrium Modeling. Vol. 1. https://doi.org/10.1016/B978-0-444-59568-3.00011-0.
Алексеев, А, Н Волчкова, И Денисова, И Левина, Н Турдыева, and Ю Халеева. 2004. “Микроэкономическая Оценка Последствий Налоговой Реформы Последствий Налоговой Реформы.” 19. Аналитические Разработки и Отчеты. Москва. www.cefir.ru/download.php?id=468.
Бадасен, П. В., Ф. С. Картаев, and А. А. Хазанов. 2015. “Эконометрическая Оценка Влияния Валютного Курса Рубля На Динамику Выпуска.” Деньги и Кредит, no. 7: 41–49.
Бахтизин, А Р. 2003. “Вычислимая Модель ‘Россия: Центр - Федеральные Округа.’” 151. Препринты ЦЭМИ РАН. Москва. sp.lan.cemi-ras.ru/pub/Working_Papers/WP-151.pdf.
Березинская, О, and А Ведев. 2015. “Производственная Зависимость Российской Промышленности От Импорта и Механизм Стратегического Импортозамещения.” Вопросы Экономики, no. 1: 103–15.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 36
Вдовиченко, А., О. Дынникова, and В. Субботин. 2003. “О Влиянии Реального Обменного Курса На Различные Сектора Российской Экономики.” Экономическая Экспертная Группа. Москва. http://www.eeg.ru/downloads/PUBLICATIONS/ANALYTICS/a20030828.pdf.
Волчкова, Наталья, Екатерина Горшкова, Сергей Лобанов, Алексей Макрушин, Наталья Турдыева, and Юлия Халеева. 2006. “Оценка Последствий Реформирования Системы Социальных Гарантий: Монетиза Ция Льгот и Реформа ЖКХ.” 25. Аналитические Разработки и Отчеты. Москва. http://cefir.ru/download.php?id=469.
Дынникова, О. В. 2000. “Макроэкономические Перспективы Укрепления Рубля и Валютная Политика.” Экономическая Экспертная Группа. Москва: ЭЭГ. www.eeg.ru/downloads/BOOK/b05.pdf.
Земницкий, А.В. 2003. “Оценка Последствий Устранения Нетарифных Барьеров Для Иностранных Компаний в Секторе Услуг Российской Экономики: Структурный Подход.” 35. Научные Труды ЦЭФИР и РЭШ. Москва. http://www.cefir.ru/download.php?id=76.
Идрисов, Г. И., Ю. Ю. Пономарев, and С.Г. Синельников-Мурылёв. 2015. “Условия Торговли и Экономическое Развитие Современной России.” Экономическая Политика 10 (3): 7–37. https://doi.org/10.18288/1994-5124-2015-3-01.
Кадочников, Павел Анатольевич, Сергей Германович Синельников-Мурылёв, and Сергей Николаевич Четвериков. 2003. Импортозамещение в Российской Федерации в 1998-2002 Гг. Институт Экономики Переходного Периода. Научные тр. Москва: Институт Экономики Переходного Периода. https://www.iep.ru/ru/publikatcii/publication/34.html.
Картаев, Ф. С. 2009. “Эконометрическое Моделирование Взаимосвязи Курса Рубля и Динамики ВВП.” Вестник Московского Университета, no. 2: 57–67.
Конторович, В.К. 2001. “Взаимосвязь Реального Курса Рубля и Динамики Промышленного Производства в России.” Экономический Журнал ВШЭ, no. №3: 363–74.
Макаров, В Л. 1999. “Вычислимая Модель Российской Экономики (RUSEC).” 99/069. Препринт ЦЭМИ. Москва.
Полбин, Андрей Владимирович. 2017. “Оценка Влияния Шоков Нефтяных Цен На Российскую Экономику в Векторной Модели Коррекции Ошибок План Презентации.” Вопросы Экономики, no. 10: 27–49.
Росстат. 2017. Национальные Счета России в 2011-2016 Годах: Статистический Сборник. Москва: Росстат.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 37
Appendix I. Analytical structure of the model
I follow notation developed in (Jensen, Rutherford, and Tarr 2004) in the description of the
analytical structure of the model.
Equations
Household’s problem
The representative household is maximizing Cobb-Douglas utility (1) subject to budget
constraint (2).
𝑈(𝐶) = ∑ 𝜃𝑖𝑙𝑜𝑔(𝑐𝑖)𝑖
(1)
Where ci - good i consumption by a representative agent, i=1,n;
С = (с1, …, ci, …. cn) – consumption basket i=1,n of the representative household;
i – Cobb-Douglas function exponent coefficient, calibrated to the cost share of the product
i in the total cost of consumption of basket C;
U(C) – utility function of a representative household.
Representative household’s budget accounts for sales taxes 𝑡𝑖𝐶 and fixed trade and
transport margins (𝝉𝒌𝒊𝒑𝒌):
(𝟏 + 𝒕𝒊𝒄)𝒑𝒊𝒄𝒊 + ∑ 𝝉𝒌𝒊𝒑𝒌
𝒌
= 𝑵 (2)
Where, N - representative agent’s disposable budget;
𝝉𝒌𝒊 − share of mark-ups of type k in costs of supplying Armington mix of good i to
a market, 𝒌 ∈ (𝒕𝒓𝒂𝒏𝒔𝒑𝒐𝒓𝒕, 𝒕𝒓𝒂𝒅𝒆).
Representative agent’s income is defined as the sum of factor returns less direct taxes:
𝑁 = 𝑤𝐿 + 𝑟𝐾𝐾 + ∑ 𝑟𝑖𝑠𝐾𝑖
𝑠 −𝑻𝑳𝑺 (3)
where 𝑤 - wage;
𝐿 – labour supply;
𝑟𝐾- mobile capital rent;
𝐾 – mobile capital supply;
𝑟𝑖𝑠 – specific capital rent in extraction industries coal, oil, natural gas, other extraction
industries;
𝐾𝑖𝑠- stock of specific factor in industry i ,
𝑻𝑳𝑺. – direct taxes.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 38
Government and investment demands in the core model assumed to be fixed on the base
year level.
Government budget
The state collects a number of indirect and direct taxes. These taxes and related ad-
valorem rates include taxes on production (𝒕𝒊𝒚), taxes on intermediate consumption (𝒕𝒊𝒋
𝒂 ), taxes on
imports (𝒕𝒊𝑴), taxes on government procurement (𝒕𝒊
𝑮), taxes on investment demand (𝒕𝒊𝑰), taxes on
exports (𝒕𝒊𝑿) and taxes on household’s consumption (𝑡𝒊
𝑪). The state budget:
∑ (1 + 𝑡𝑖𝐺 )𝒑𝒊𝒂𝒊
𝑮
𝑖= 𝑻𝒀 + 𝑻𝒂 + 𝑻𝑀 + 𝑻𝑮 + 𝑻𝑰 + 𝑻𝑿 + 𝑻𝑪 + 𝑻𝑭𝑺 + 𝑻𝑳𝑺 (4)
Where
Tk – revenue from a tax k;
𝑻𝑭𝑺 – revenue from taxes on factors of production;
𝑻𝑳𝑺. – revenue from direct taxes.
It is assumed in the core model that government consumption is fixed in real terms in the
core government sector’s demand is fixed on the base year level: 𝒂𝒊𝑮 = 𝐺�̅�. Adjustment of the
implicit savings of a representative agent compensates for changes in cost of government
consumption due to changes in prices and tax revenues.
Supply for domestic and export markets
Domestically produced goods and services supplied to domestic and international
markets. A constant elasticity of transformation (CET) function describes transformation
possibilities between domestic (𝒅𝒊) and export (𝒆𝒊) supplies of domestic output (Yi). Sales shares
in the country and abroad are determined by relative prices, provided that firms produce final
goods in order to minimize cost subject to CET production function:
𝑌𝑖 = �̅�𝑖 [𝜃𝐷 (𝒅𝒊
𝐷𝑖
)
1+𝜂𝜂
+ (1 − 𝜃𝐷) (𝒆𝒊
𝐸𝑖
)
1+𝜂𝜂
]
𝜂1+𝜂
(5)
In this equation, the parameters are:
base year supply for domestic market (𝐷𝑖)
and export (𝐸𝑖) markets,
level of the base year production �̅�,
D – the share parameter of the CET function, calibrated to domestic sales in total sales
of the base year,
and 𝜂 – elasticity of transformation between supply to domestic and export markets.
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 39
Associated cost function, i.e. the cost of supply of sector i in the domestic and export
market is denoted by 𝑪𝑬𝑻 (𝒑𝒊𝑫, 𝒑𝒊
𝑿).
Production technology is described by the nested Leontief production function: output
depends on the volume of consumption of intermediate goods, 𝑎𝑚𝑖, (where m=1,n) and primary
factors of production, mobile labor 𝐿𝑖 and capital 𝐾𝑖 , and specific 𝐾𝑖𝑠 capital.
Producers demand intermediate goods and factors in order to minimize production costs
for a given volume of products under the technological constraint (production function):
𝑌𝑖 = �̅�𝑖 min [𝑎𝑚𝑖 , 𝑉𝐴𝑖(𝐿𝑖 , 𝐾𝑖 , 𝐾𝑖𝑠)] (6)
where 𝑎𝑚𝑖 = (𝑎𝑚1,𝑖 , 𝑎𝑚2,𝑖 , … ) – intermediate goods used in production of good i.
𝑉𝐴𝑖(𝐿𝑖 , 𝐾𝑖 , 𝐾𝑖𝑠) – value added, a Cobb-Douglas mixture of primary factors.
Balance of payments
In the main version of the model, the current account balance is fixed in real terms on the
level of the base year. Current account is the difference between value of exports and imports
𝑝𝑖
𝑋− exogenous world export prices;
𝒆𝒊 – volume of exports (in real terms);
𝑝𝑖
𝑀− exogenous world prices for imported goods;
𝒎𝒊 – volume of imports (in real terms).
The increase (decrease) in imports should be compensated by a corresponding reduction
(increase) in exports, while maintaining a fixed surplus of the current account at the level of the
base year (�̅�)
∑ 𝑝𝑖
𝑋𝒆𝒊 = ∑ 𝑝
𝑖
𝑀𝒎𝒊 + �̅� ⊥ 𝝆 (7)
Following work of Lars Mathiesen (Mathiesen 1985), which show that the Arrow – Debreu
equilibrium can be formulated and solved as a sequence of complementary problems, the
arbitrage and market clearing conditions are presented in the complementary slackness format.
The balance of payments constrains is the market equilibrium constraint that has
exchange rate as a complimentary variable (𝝆).
Arbitrage conditions
Production of a good i would take place if equation (8) holds, or in terms of complementary
slackness formulation: (8) ⊥ 𝒀𝒊.
The cost of supply of sector i in the domestic and export market 𝑪𝑬𝑻 (𝒑𝒊𝑫, 𝒑𝒊
𝑿) is equal to
the cost of production 𝑪𝑶𝑺𝑻𝑌(𝑝𝑖𝑗𝑚 , 𝑝𝑖 , 𝑤, 𝑟𝐾 , 𝒓𝒊
𝑺). Primary factors of production and intermediates
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 40
are connected in a nested production function with a constant elasticity of substitution (CES)
𝑪𝑶𝑺𝑻𝑌(𝑝𝑖𝑗𝑚 , 𝑝𝑖 , 𝑤, 𝑟𝐾 , 𝒓𝒊
𝑺) which includes:
- intermediate goods (price of intermediate goods j used in the production of good i (𝑝𝑖𝑗𝑚);
- price of bundled services for intermediate and final consumption 𝒑𝒊𝑺
- labour (wage - 𝑤);
- mobile capital (mobile capital rent - 𝑟𝐾)
- and specific capital (specific capital rent - 𝒓𝒊𝑺):
𝒀𝒊.⊥ 𝑪𝑬𝑻𝒚(𝒑𝒊𝑫, 𝒑𝒊
𝑿) = 𝑪𝑶𝑺𝑻𝑺𝒚(𝑝𝑖𝑗𝑚 , 𝑝𝑖 , 𝑤, 𝑟𝐾 , 𝒓𝒊
𝑺) (8)
Where 𝒑𝒊𝑫 – price of a domestically produced good i for domestic market ;
𝒑𝒊𝑿 – domestic price of a good i for the export market.
⊥ 𝒂𝒊 Bundling of domestic and imported goods for different markets:
Price of goods (𝒑𝒊) reflects the cost 𝑪𝑬𝑺𝑨(𝒑𝒊𝑫, 𝒑𝒊
𝑴) of domestic (𝒑𝒊𝑫) and imported
resources (𝒑𝒊𝑴), as well as the associated trade and transport margins (𝒑𝒌):
𝒂𝒊 ⊥ 𝒑𝒊 = 𝑪𝑬𝑺𝑨(𝒑𝒊𝑫, 𝒑𝒊
𝑴) + ∑ 𝝉𝒌𝒊𝒑𝒌
𝒌
(9)
Where 𝝉𝒌𝒊 - share of mark-ups of type k in costs of supplying Armington mix (a
bundle of domestic and imported goods) of good i to a market (differs for each separate
market: for final consumption of households, government, investment, and intermediate
goods’ markets).
Two bundling processes are described by (9): aggregation on the industry and product
level of intermediate goods, and bundling of intermediate services and goods for final
consumption by households, government and investment sector.
Intermediate consumption of goods (𝒂𝒊𝒋𝒎) priced (𝒑𝒊𝒋
𝒎), for intermediate consumption of
industry i of good j. Note that services are not aggregated this way – firms in the industry demand
services for intermediate consumption on the final market. The equation below is presented with
an associated complementarity condition:
𝒂𝒊𝒋𝒎 ⊥ 𝒑𝒊𝒋
𝒎 = 𝑪𝑬S𝑖𝑗𝑚(𝒑𝒋
𝑫, 𝒑𝒋𝑴) + ∑ 𝝉𝒌𝒊𝒑𝒌𝒌 ; (9-a)
Where 𝑪𝑬S𝑖𝑗𝑚(𝒑𝒋
𝑫, 𝒑𝒋𝑴) – cost of supplying a bundle of domestic and imported intermediate
goods.
Intermediate consumption of services (𝒂𝒊𝑺) priced (𝒑𝒊 ), with an associated
complementarity condition:
𝒂𝒊𝑺 ⊥ 𝒑𝒊 = 𝑪𝑬𝑺𝑨(𝒑𝒊
𝑫, 𝒑𝒊𝑴) + ∑ 𝝉𝒌𝒊𝒑𝒌
𝒌
, 𝑓𝑜𝑟 𝑖 ∈ {𝑠𝑒𝑟𝑣𝑖𝑐𝑒𝑠} (9-b)
⊥ 𝒆𝒊 Domestic price of exports is equal to the exogenous (FOB) price of the world market
(expressed in the world currency) ( �̅�𝒊𝑿), multiplied by the exchange rate (𝝆):
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 41
𝒆𝒊 ⊥ 𝒑𝒊𝑿 = �̅�𝒊
𝑿 ⋅ 𝝆 (10)
⊥ 𝒎𝒊 Domestic price of imports is equal to the exogenous (CIF) price of the world market
(expressed in foreign currency) �̅�𝒊𝑴, multiplied by the exchange rate (𝝆):
𝒎𝒊 ⊥ 𝒑𝒊𝑴 = �̅�𝒊
𝑴 ⋅ 𝝆 (11)
Free entry guarantees zero profit in all industries. This means that gross income is equal
to the sum of all production costs.
Market equilibrium conditions
⊥ 𝑝𝑖 Commodity markets: aggregate supply is equal to aggregate demand on each
market:
𝒂𝒊 = 𝒄𝒊 + 𝒂𝒊𝑰 + 𝒂𝒊
𝑮 + ∑ 𝒂𝒊𝒋𝑺
𝒋 ⊥ 𝑝𝑖,
𝒂𝒊𝒋𝑺 = 𝒀𝒊.
𝝏𝑪𝑶𝑺𝑻𝒊𝒚
𝝏𝒑𝒋
, j ∈ {𝑠𝑒𝑟𝑣𝑖𝑐𝑒𝑠} (12)
in the core model investment sector’s demand is fixed on the base year level: 𝒂𝒊𝑰 = 𝐼�̅�;
government sector’s demand is fixed on the base year level: 𝒂𝒊𝑮 = 𝐺�̅�; This formulation
of demand utilizes Shephard's lemma, stating that conditional factor demand for each
input factor is the derivative of the cost function.
⊥ 𝒑𝒊𝒋𝒎 Supply of intermediate goods equals demand
𝒂𝒊𝒋𝒎 = 𝒀𝒊.
𝝏𝑪𝑶𝑺𝑻𝒊𝒚
𝝏𝒑𝒊𝒋𝒎 ⊥ 𝒑𝒊𝒋
𝒎 (13)
⊥ 𝒑𝒊𝑫 Domestic goods markets: the supply of domestic goods equals to the demand for
domestically produced goods and services from all markets:
𝒅𝒊 = ∑ 𝒂𝒊𝒋𝒎 𝝏𝑪𝑬S𝑖𝑗
𝑚(𝒑𝒋𝑫,𝒑𝒋
𝑴)
𝝏𝒑𝒋𝑫𝒋 + 𝒂𝒊
𝝏𝑪𝑬𝑺𝐴(𝒑𝒊𝑫,𝒑𝒊
𝑴)
𝝏𝒑𝒊𝑫 (14)
⊥ 𝒑𝒊𝑴 Import markets: total imports include sales of aggregate demand plus sales to firms
for intermediate consumption:
𝒎𝒊 = ∑ 𝒂𝒊𝒋𝒎 𝝏𝑪𝑬S𝑖𝑗
𝑚(𝒑𝒋𝑫,𝒑𝒋
𝑴)
𝝏𝒑𝒋𝑴𝒋 + 𝒂𝒊
𝝏𝑪𝑬𝑺𝑨(𝒑𝒊𝑫,𝒑𝒊
𝑴)
𝝏𝒑𝒊𝑀 (15)
⊥ 𝒘𝓵 The supply of labor is equal to the demand for labor:
�̅� = ∑ 𝒚𝒊
𝝏𝑪𝑶𝑺𝑻𝒊𝒚
𝝏𝒘𝓵𝒊
(16)
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 42
Where �̅� - total supply of labour, fixed on the level of the base year;
⊥ 𝒓𝑲 Capital supply equals demand for capital:
�̅� = ∑ 𝒚𝒊𝝏𝑪𝑶𝑺𝑻𝒊
𝒚
𝝏𝒓𝑲𝒊 (17)
Where �̅� – total supply of mobile capital, fixed on the level of the base year (core model
formulation);
⊥ 𝑟𝑖𝑠 The supply of firm-specific capital equals the demand for specific capital by the firm i:
𝐾𝑖𝑠 = 𝒂𝒊
𝝏𝑪𝑬𝑺𝒊𝑨
𝝏𝒓𝒊𝒔 (18)
Where 𝐾𝑖𝑠 – fixed supply of specific capital in industry i .
Symbol map
Table 5. Symbols used in the analytical description of the model
Symbol
Definition (in the order of appearance in the Appendix I)
1 𝐷𝑖 benchmark production for domestic market of good i, where i=1,n
2 𝐸𝑖 benchmark exports of good i, where i=1,n
3 𝐺�̅� the base year government demand
4 𝐼�̅�; the base year investment demand
5 𝑝𝑖
𝑀 exogenous world prices for imported goods
6 𝑝𝑖
𝑋 exogenous world export prices
7 �̅�𝑖 domestic output of good i in the benchmark equilibrium of the base year, where i=1,n
8 𝒂𝒊𝑮 government consumption of good i
9 𝒂𝒊𝑺 Armington mix of services (domestic and import
bundle) for final and intermediate consumption 10 𝒂𝒊 supply of an Armington mix (a bundle of domestic
and imported goods) for final markets (household, government and investment)
11 𝒂𝒊𝒋𝒎 Armington mix of goods (domestic and import bundle)
for intermediate consumption 12 𝒄𝒊 good i consumption by a representative agent, i=1,n;
13 𝑪𝑬S𝑖𝑗𝑚(𝒑𝒋
𝑫, 𝒑𝒋𝑴) cost of supplying a bundle of domestic and imported
intermediate goods j to industry i 14 𝑪𝑶𝑺𝑻𝑌(𝑝𝑖𝑗
𝑚 , 𝑝𝑖𝑆, 𝑤, 𝑟𝐾 , 𝒓𝒊
𝑺) cost of production of good 𝐘𝐢 with a nested
production function 15 𝒅𝒊 supplies of good i for the domestic market, where
i=1,n 16 𝒆𝒊 exports of good i, where i=1,n 17 𝐾𝑖
𝑠 stock of specific factor in industry i
18 �̅� mobile capital supply
19 �̅� labour supply
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 43
Symbol
Definition (in the order of appearance in the Appendix I)
20 𝒎𝒊 volume of imports (in real terms) 21 𝒑𝑮 price index on government procurement 22 𝒑𝒊
𝑫 price of a domestically produced good i for domestic market
23 𝒑𝒊𝑴 domestic price of imports
24 𝒑𝒊𝑿 domestic price of a good i for the export market
25 𝑝𝑖 price of a good (Armington bundle of domestic and imported goods) i on the final goods’ market (final goods and services are consumed by households, government and investment sector), where i=1,n
26 𝑝𝑖𝑗𝑚 price of intermediate goods
27 𝒑𝒌 Price of service k, used for supplying goods to markets (transport or trade services)
28 𝑟𝑖𝑠 specific capital rent in extraction industries coal (s10),
oil, natural gas, other extraction industries (s12x); 29 𝑟𝐾 rent
30 𝑻𝒂 revenue from taxes on intermediate consumption 𝐭𝐢𝐣𝐚
31 𝑻𝑪 revenue from taxes on household’s consumption t𝐢𝐂
32 𝑻𝑭𝑺 revenue from taxes on factors of production
33 𝑻𝑮 revenue from taxes on government procurement 𝐭𝐢𝐆
34 𝑡𝑖𝐶 sales tax rates on good i, where i=1,n
35 𝑻𝑰 revenue from taxes on investment demand 𝐭𝐢𝐈
36 𝑻𝑳𝑺 direct taxes
37 𝑻𝑴 revenue from taxes on imports 𝐭𝐢𝐌
38 𝑻𝑿 revenue from taxes on exports 𝐭𝐢𝐗
39 𝑻𝒀 revenue from taxes on production 𝐭𝐢𝐲
40 �̅� fixed surplus of the current account at the level of the base year а
41 𝑌𝑖 domestic output of good i, where i=1,n
42 𝜃𝐷 the share parameter of the CET function, calibrated to domestic sales in total sales of the base year
43 𝜃𝑖 Cobb-Douglas function exponent coefficient, equal to the cost share of the product i in the total cost of consumption of basket C;
44 𝝉𝒌𝒊 share of mark-ups of type k in costs of supplying Armington mix of good i to a market
45 𝑪 = (𝒄𝟏, … , 𝒄𝒏) consumption basket i=1,n of the representative household;
46 𝑪𝑬𝑺𝑨(𝒑𝒊𝑫, 𝒑𝒊
𝑴) cost of producing an Armington mix of domestic and imported goods for final (household, government and investment consumption) and intermediate markets
47 𝑪𝑬𝑻 (𝒑𝒊𝑫, 𝒑𝒊
𝑿) cost of production of good 𝐝𝐢 for domestic market and good 𝐞𝐢 for the export market with a CET production function
48 𝑁 representative agent’s income
49 𝑈(𝐶) utility function of a representative household
50 𝑉𝐴𝑖 VAi(Li, Ki, Kis) – value added, a Cobb-Douglas mixture
of primary factors 51 𝑤 wage
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 44
Symbol
Definition (in the order of appearance in the Appendix I)
52 𝜂 elasticity of transformation between supply to domestic and export markets
53 𝝆 exchange rate (in terms of units of local currency to a unit of foreign currency used for pricing of the country’s exports and imports)
54 𝜂 elasticity of transformation between supply to domestic and export markets
55 𝜎𝑚 elasticity of substitution between domestic and imported goods in intermediate consumption
56 𝜎𝑌 elasticity of substitution between value added and intermediate goods in the production function
57 𝜎𝑉𝐴 elasticity of substitution between different factors in production of value added
58 𝜎𝐴 elasticity of substitution between domestic and imported goods in the Armington aggregation function for production of final goods
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 45
Appendix II Data and parametrization
Industry list
Table 6. Activities and commodity groups presented in the model
# Code Short name of activity / commodity group
1 s01 Agriculture
2 s02 Logging
3 s05 Fishery
4 s10 Coal and peat
5 oil Crude oil
6 gas Natural gas
7 s112 Services related to oil and gas prod.
8 s12x Other minerals
9 s15 Food products
10 s15x Beverages
11 s16 Tobacco products
12 s17 Textile products
13 s18 Clothes and fur
14 s19 Leather products
15 s20 Wood
16 s21 Paper
17 s22 Publishing and printing
18 s23 Coke and petrochemical products
19 s24 Chemical products
20 s25 Rubber and plastic products
21 s26 Other non-metallic mineral products
22 s27 Metals
23 s28 Finished metal products
24 s29 Machinery and equipment
25 s30 Office equipment and computers
26 s31 Electrical machinery
27 s32 Radio, television and communication equipment
28 s33 Precision and optical instruments
29 s34 Motor vehicles
30 s35 Other transport equipment
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 46
# Code Short name of activity / commodity group
31 s36x Furniture, recycling
32 s40 Power supply, steam and hot water
33 s41 Collection and distribution of water
34 s45 Construction
35 trd Trade
36 s55 Hotels and restaurants
37 trn Transport
38 s63 Auxiliary modes of transport
39 s64 Post and telecommunications
40 s65x Financial intermediation and insurance
41 s70 Real estate activities
42 s71 Rent of machinery and equipment
43 s72 Computer and related activities
44 s73 Research and development
45 s74 Other business services
46 s75 Public administration and defense
47 s80 Education
48 s85 Health and social work
49 s90 Sanitation and waste management
50 s91 Activities of membership organizations
51 s92 Recreational cultural and sporting events
52 s93x Other activities, domestic work
Source: author
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 47
Appendix III Simulations design
Table 7. Changes in import prices to 2011 by commodity group, part 1
Source: author’s estimates, COMTRADE, CEPII TUV databases
Table 8. Changes in import prices to 2011 by commodity group, part 2
Source: Author’s estimates, COMTRADE, CEPII TUV databases
2012 2013 2014 2015 2016
01 Agriculture -9% -25% -6% -21% -18%
02 Forestry 2% 13% -2% 3% -11%
05 Fishing -1% 12% 17% -68% -66%
10 Mining of coal 37% 33% -44% -53% -63%
15 Food 9% 12% 11% -20% -24%
15 -9 Beverages 0% 8% -3% -24% -25%
16 Tobacco products -6% 1% -7% -12% -20%
17 Textiles 17% 16% 19% 9% 12%
18 Wearing apparel 23% 32% 34% 22% 21%
19 Leather 4% 11% 21% 23% 36%
20 Wood products 56% 60% 76% 34% 24%
21 Paper products 11% 4% -1% -16% -17%
Change in import prices to 2011
2012 2013 2014 2015 2016
22 Publishing 2% 8% -10% 2% 11%
23 Refined petroleum 55% 87% 37% 50% 48%
24 Chemicals -4% -1% -8% -33% -30%
25 Plastic products 8% 0% 2% -9% -6%
26 Non-metallic products 22% 33% 19% 16% 22%
28 Metal products 54% 51% 26% 12% 13%
29 Machinery 6% 8% 8% 0% 2%
30 Office machinery -6% 15% 21% 22% 27%
31 Electrical machinery 14% 14% 10% 3% 0%
32 Radio television 0% 0% 0% 0% 0%
33 Medical instruments 1% 6% 4% -15% -13%
34 Motor vehicles 0% 4% -3% -22% -17%
Change in import prices to 2011
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 48
Appendix IV Simulation results
Table 9. Impact of the terms of trade shock in the Central scenario and it’s components, static model, results are percentage changes from the base year
Source: author’s estimates
Central
scenario
Oil
scenario
Natural gas
scenario
Petroleum
products
scenario
World price change
Crude oil -10% -10%
Natural gas -3% -3%
Petroleum products -8% -8%
Aggregate welfare
Welfare (EV as % of consumption) -1,169 -0,681 -0,099 -0,387
Welfare (EV as % of GDP) -0,577 -0,335 -0,048 -0,189
GDP decomposition
GDP (% change) -1,545 -0,989 -0,095 -0,440
Real private consumption (C % change) -1,169 -0,681 -0,099 -0,387
Real government consumption (G % change) -4,277 -2,942 -0,178 -1,052
Real investment demand (I % change) -0,874 -0,543 -0,060 -0,263
Real aggregated exports (E % change) 1,226 0,887 -0,005 0,288
Real aggregated imports (M % change) -5,384 -3,262 -0,498 -1,667
RER and CPI
Real exchage rate (% change) 4,236 2,538 0,376 1,208
Consumer price index (% change) 0,000 0,000 0,000 0,000
Return to primary factors
Labor (w % change) -1,333 -0,836 -0,113 -0,372
Mobile capital (r % change) -0,726 -0,371 -0,072 -0,282
Crude oil resources (% change) -3,222 -2,589 0,468 -1,075
Natural gas resources (% change) 4,196 5,978 -3,885 2,631
Coal resources (% change) 4,264 2,689 0,452 0,966
Other mining resources (% change) 5,937 3,561 0,568 1,619
Aggregated production
Aggregated production index (% change) 0,569 0,363 0,059 0,134
Argiculture production index (% change) 0,080 0,048 0,010 0,023
Extraction production index (% change) 0,004 -0,008 0,012 0,001
Manufacturing production index (% change) 0,907 0,568 0,109 0,207
Services production index (% change) -0,422 -0,245 -0,072 -0,096
Factor adjustment
Mobile capital (% changing sectors) 0,657 0,435 0,124 0,207
Labor (% changing sectors) 1,138 0,772 0,102 0,301
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 49
Table 10. Impact of the terms of trade shock in the Central scenario and it’s components, stationary model, results are percentage changes from the base year
Source: author’s estimates
Central
scenario
Oil
scenario
Natural gas
scenario
Petroleum
products
scenario
World price change
Crude oil -10% -10%
Natural gas -3% -3%
Petroleum products -8% -8%
Aggregate welfare
Welfare (EV as % of consumption) -2,464 -1,412 -0,227 -0,868
Welfare (EV as % of GDP) -1,229 -0,697 -0,111 -0,425
GDP decomposition
GDP (% change) -2,510 -1,532 -0,190 -0,797
Real private consumption (C % change) -2,464 -1,412 -0,227 -0,868
Real government consumption (G % change) -5,213 -3,465 -0,269 -1,394
Real investment demand (I % change) -1,562 -0,931 -0,128 -0,517
Real aggregated exports (E % change) 0,427 0,438 -0,083 -0,005
Real aggregated imports (M % change) -6,506 -3,907 -0,614 -2,097
RER and CPI
Real exchage rate (% change) 4,301 2,574 0,382 1,230
Consumer price index (% change) 0,000 0,000 0,000 0,000
Return to primary factors
Labor (w % change) -2,609 -1,555 -0,239 -0,845
Mobile capital (r % change) -0,076 -0,007 -0,008 -0,044
Crude oil resources (% change) -4,024 -3,046 0,386 -1,379
Natural gas resources (% change) 3,241 5,441 -3,972 2,287
Coal resources (% change) 3,365 2,188 0,366 0,642
Other mining resources (% change) 5,142 3,124 0,494 1,337
Aggregated production
Aggregated production index (% change) -0,347 -0,150 -0,030 -0,201
Argiculture production index (% change) 0,029 0,020 0,005 0,004
Extraction production index (% change) -0,056 -0,042 0,006 -0,021
Manufacturing production index (% change) 0,730 0,469 0,092 0,143
Services production index (% change) -1,050 -0,597 -0,133 -0,327
Factor adjustment
Mobile capital (% changing sectors) 2,007 1,167 0,241 0,704
Labor (% changing sectors) 1,284 0,855 0,113 0,349
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 50
Table 11. Changes in real production, exports, imports and household’s consumption in the Central scenario, comparative static model
Source: author’s estimates
Short name of activity /
commodity group
Change in
production
Change in
exports
Change in
imports
Change in HH
consumption
Agriculture 2,10 2,90 -9,54 -1,15
Logging 1,58 2,51 -0,55 -0,26
Fishery 1,28 1,70 -3,73 -2,10
Coal and peat 3,64 4,33 -1,09 0,39
Crude oil -1,74 -2,29 -10,39
Natural gas 3,55 2,88 -6,70
Services related to oil and gas prod. 0,37 0,94 -10,21 -5,19
Other minerals 4,82 5,13 2,62 -1,32
Food products 1,70 2,45 -9,48 -0,99
Beverages 1,68 2,46 -13,79 -0,84
Tobacco products -0,52 0,16 -9,80 -0,93
Textile products 6,91 7,51 -3,39 -2,07
Clothes and fur 7,97 8,64 -5,06 -1,84
Leather products 19,32 19,58 -4,65 -2,28
Wood 3,01 3,84 -5,19 -0,05
Paper 2,76 3,48 -2,03 -1,51
Publishing and printing -0,08 1,10 -9,55 -0,90
Coke and petrochemical products -0,63 -1,70 -6,06 -5,71
Chemical products 7,42 7,06 -3,28 -1,67
Rubber and plastic products 2,82 3,62 -1,53 -1,60
Other non-metallic mineral products 0,62 1,42 -2,74 -1,22
Metals 5,21 6,05 -3,11 0,87
Finished metal products 3,56 4,63 -3,03 -1,63
Machinery and equipment 8,55 9,05 -5,22 -2,06
Office equipment and computers 10,63 9,80 -1,99 -3,00
Electrical machinery 5,65 6,45 -3,06 -1,72
Radio, television and communication equipment 8,32 7,74 -2,97 -1,99
Precision and optical instruments 8,17 6,88 -7,95 -1,88
Motor vehicles 4,59 5,24 -5,13 -2,75
Other transport equipment 9,46 9,40 -14,06 -1,55
Furniture, recycling 6,87 7,48 -12,26 -1,33
Power supply, steam and hot water 0,58 1,45 -4,81 0,10
Collection and distribution of water 0,23 0,97 -5,92 0,01
Construction -0,59 0,19 -14,44 -0,55
Trade 0,02 0,91 -18,23 -0,39
Hotels and restaurants -1,05 -0,20 -0,72
Transport 0,57 1,09 -17,08 -0,85
Auxiliary modes of transport 0,42 1,15 -0,27
Post and telecommunications -0,62 0,08 -0,58
Financial intermediation and insurance 0,70 1,45 -18,60 -0,24
Real estate activities -0,37 0,44 -18,17 -0,41
Rent of machinery and equipment 1,14 1,80 -18,29 -0,37
Computer and related activities -0,22 0,46 -17,23 -0,32
Research and development -1,25 -0,15 -18,26
Other business services 0,82 1,29 -20,82 0,29
Public administration and defense -3,95 -3,24 -0,43
Education -3,63 -2,83 -18,79 -0,16
Health and social work -3,61 -2,87 -17,85 -0,54
Sanitation and waste management -2,55 -0,77 -0,78
Activities of membership organizations -3,94 -0,31
Recreational cultural and sporting events -1,84 -1,09 -15,75 -0,44
Other activities, domestic work -0,20 -0,05
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 51
Table 12. Changes in production, exports, imports and household’s consumption in the Central scenario, steady-state model
Source: author’s estimates
Short name of activity /
commodity group
Change in
production
Change in
exports
Change in
imports
Change in HH
consumption
Agriculture 0,77 1,54 -10,49 -2,55
Logging 0,78 1,73 -1,52 -1,47
Fishery 0,09 0,52 -5,02 -3,36
Coal and peat 2,99 3,71 -2,03 -0,70
Crude oil -2,67 -3,22 -11,26
Natural gas 2,73 2,06 -7,73
Services related to oil and gas prod. -0,34 0,25 -11,52 -6,49
Other minerals 4,31 4,65 1,91 -2,52
Food products 0,46 1,22 -10,75 -2,28
Beverages 0,49 1,28 -15,26 -2,10
Tobacco products -1,88 -1,22 -10,81 -2,30
Textile products 6,28 6,91 -4,64 -3,33
Clothes and fur 7,26 7,96 -6,41 -3,12
Leather products 19,25 19,53 -6,02 -3,56
Wood 2,26 3,13 -6,28 -1,22
Paper 1,76 2,49 -3,17 -2,78
Publishing and printing -1,00 0,22 -11,14 -2,08
Coke and petrochemical products -1,59 -2,67 -6,84 -7,10
Chemical products 6,60 6,25 -4,28 -2,96
Rubber and plastic products 2,04 2,88 -2,48 -2,84
Other non-metallic mineral products -0,13 0,72 -3,73 -2,42
Metals 4,73 5,58 -3,81 -0,35
Finished metal products 3,01 4,14 -4,05 -2,83
Machinery and equipment 8,42 8,96 -6,36 -3,28
Office equipment and computers 10,53 9,63 -2,91 -4,28
Electrical machinery 5,29 6,13 -3,98 -2,95
Radio, television and communication equipment 8,10 7,50 -3,97 -3,21
Precision and optical instruments 8,27 6,87 -9,36 -3,05
Motor vehicles 4,01 4,70 -6,27 -3,98
Other transport equipment 9,68 9,63 -16,01 -2,67
Furniture, recycling 6,27 6,91 -13,75 -2,56
Power supply, steam and hot water -0,34 0,57 -5,81 -1,02
Collection and distribution of water -0,54 0,22 -7,06 -0,74
Construction -1,32 -0,52 -15,48 -1,75
Trade -1,03 -0,13 -19,52 -1,69
Hotels and restaurants -2,24 -1,36 -1,96
Transport -0,37 0,15 -18,79 -1,99
Auxiliary modes of transport -0,51 0,26 -1,31
Post and telecommunications -1,78 -1,06 -1,84
Financial intermediation and insurance -0,24 0,55 -20,48 -1,30
Real estate activities -1,84 -1,05 -18,37 -2,15
Rent of machinery and equipment 0,24 0,84 -18,61 -2,06
Computer and related activities -1,15 -0,41 -18,63 -1,44
Research and development -1,95 -0,75 -20,90
Other business services -0,04 0,47 -22,51 -0,72
Public administration and defense -4,88 -4,10 -1,24
Education -4,50 -3,57 -22,12 -0,61
Health and social work -4,48 -3,64 -20,86 -1,14
Sanitation and waste management -3,60 -1,70 -1,76
Activities of membership organizations -4,85 -0,92
Recreational cultural and sporting events -2,69 -1,89 -17,68 -1,35
Other activities, domestic work -0,56 -0,42
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 52
Table 13. Changes in prices of output, industry revenues, costs of intermediates in production of manufactured goods and services, in the Central scenario, static model
Source: author’s estimates
Short name of activity /
commodity group
Change in output
price, %
Change in industry
revenue, %
Change in the price index of
intermediate products, %
Agriculture -0,44 -0,42 0,07
Logging 0,21 0,09 1,39
Fishery 1,82 1,16 3,32
Coal and peat 0,25 0,22 -0,18
Crude oil -1,69 -1,26 -0,47
Natural gas 0,14 0,22 -0,57
Services related to oil and gas prod. -0,61 -0,61 -0,40
Other minerals 1,02 0,81 0,46
Food products -0,19 -0,20 0,05
Beverages -0,40 -0,41 -0,09
Tobacco products 0,63 0,61 2,05
Textile products 0,56 0,49 1,36
Clothes and fur 0,33 0,26 1,58
Leather products 0,10 0,05 0,81
Wood -0,84 -0,82 -0,73
Paper 0,16 0,03 0,68
Publishing and printing -0,57 -0,56 -0,20
Coke and petrochemical products 2,84 2,01 3,36
Chemical products 0,51 0,47 1,32
Rubber and plastic products -0,05 -0,09 0,22
Other non-metallic mineral products -0,50 -0,50 -0,22
Metals -0,91 -0,88 -0,91
Finished metal products -1,50 -1,40 -1,61
Machinery and equipment -0,68 -0,70 -0,43
Office equipment and computers 1,00 0,74 1,99
Electrical machinery -1,01 -0,97 -0,94
Radio, television and communication equipment 0,58 0,46 1,55
Precision and optical instruments -0,45 -0,47 0,15
Motor vehicles 0,91 0,83 1,49
Other transport equipment -1,06 -1,02 -0,98
Furniture, recycling -1,15 -1,12 -1,22
Power supply, steam and hot water -1,23 -1,21 -1,43
Collection and distribution of water -1,18 -0,89 -0,65
Construction -0,54 -0,54 -0,07
Trade -0,79 -0,71 -0,36
Hotels and restaurants -0,45 -0,46
Transport -0,23 -0,25 0,39
Auxiliary modes of transport -0,44 -0,45
Post and telecommunications -0,46 -0,46
Financial intermediation and insurance -0,85 -0,85 -0,50
Real estate activities -0,74 -0,74 -0,62
Rent of machinery and equipment -0,73 -0,73 -0,06
Computer and related activities -0,42 -0,43 0,44
Research and development -0,62 -0,64 -0,08
Other business services -0,75 -0,75 -0,20
Public administration and defense -0,74 -0,74
Education -1,06 -1,06 -0,47
Health and social work -0,64 -0,64 0,51
Sanitation and waste management -0,26 -0,37
Activities of membership organizations -0,86
Recreational cultural and sporting events -0,74 -0,74 -0,21
Other activities, domestic work -1,11
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 53
Table 14. Social accounting matrix for 2011, trln (10**12) Rub, nominal prices
Source: author’s estimates
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26cagr cext cmnf ctrn ctrd csrv aagr aext amnf atrn atrd asrv trsc lab cap T_Y S_Y T_F T_FY T_D gov hh ent s-i row tot
1 cagr 0,725 0,001 1,518 0,004 0,011 0,119 0,036 1,315 0,176 0,214 4,117
2 cext 0,004 0,352 2,728 0,033 0,071 0,534 0 0,009 0,589 3,512 7,832
3 cmnf 0,644 0,517 8,164 0,956 0,55 4,458 0,099 7,673 5,252 5,654 33,966
4 ctrn 0,072 0,473 0,968 0,943 1,802 0,557 0,672 0,102 0,948 0,647 7,184
5 ctrd 0,042 0,096 0,099 0,041 0,331 0,074 12,791 0,171 0,001 13,646
6 csrv 0,245 0,859 2,679 1,534 2,215 9,404 10,452 9,519 7,728 0,774 45,409
7 aagr 3,58 0 0,342 0,011 0,013 0,027 3,974
8 aext 0,001 6,753 0,407 0,027 0,027 0,146 7,361
9 amnf 0,034 0,766 23,377 0,065 0,517 0,338 25,097
10 atrn 0,002 0,005 0,03 6,543 0,056 0,155 6,791
11 atrd 0,003 0,03 0,41 0,206 12,849 0,703 14,2
12 asrv 0,004 0,017 0,386 0,07 0,182 42,877 43,537
13 trsc 0,178 0,099 1,798 0,188 0,118 1,76 0,06 6,427 0,809 2,026 13,463
14 lab 0,373 0,574 2,188 1,163 2,259 9,741 16,297
15 cap 1,64 4,158 4,06 1,454 6,182 13,782 31,277
16 T_Y 0,023 0,015 0,166 0,062 0,023 0,626 0,004 3,245 0,182 3,852 8,198
17 S_Y -0,056 -0,056
18 T_F 0,084 0,151 0,641 0,355 0,58 2,151 3,962
19 T_FY 0,068 0,089 0,058 0,058 0,332 0,605
20 T_D 2,168 2,451 4,619
21 gov 8,198 -0,056 3,962 0,605 4,619 17,328
22 hh 16,297 22,219 38,516
23 ent 31,277 31,277
24 s-i 1,088 7,041 6,607 14,736
25 row 0,493 0,26 9,014 0,261 0,003 1,163 5,487 16,68
26 tot 4,117 7,832 33,966 7,184 13,646 45,409 3,974 7,361 25,097 6,791 14,2 43,537 13,463 16,297 31,277 8,198 -0,056 3,962 0,605 4,619 17,328 38,516 31,277 14,736 16,68
EFFECTS OF TERMS OF TRADE SHOCKS ON THE RUSSIAN ECONOMY OCTOBER 2019 54
Table 15. Key for SAM rows
# Code Description # Code Description
1 cagr goods of agricuture industires 14 lab factrors of production: labour
2 cext goods of extraction industires 15 cap factrors of production: capital
3 cmnf goods of manufacturing industires 16 T_Y taxes: excises
4 ctrn goods of transportation industires 17 S_Y subsidies on production
5 ctrd goods of trade industires 18 T_F taxes on factors of production
6 csrv activities of services industires 19 T_FY taxes on production
7 aagr activities of agricuture industires 20 T_D direct taxes
8 aext activities of extraction industires 21 gov government
9 amnf activities of manufacturing industires 22 hh households
10 atrn activities of transportation industires 23 ent enterprises
11 atrd activities of trade industires 24 s-i savings-investment account
12 asrv activities of services industires 25 row rest of the world account (row of imports and column of exports)
13 trsc transaction markups 26 tot totals
Source: author